Databricks Architect Jobs

Databricks Architect

Tiger Analytics

United States

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world. This role will be responsible for Databricks Architecture, Designing and implementing best data practices. Requirements Strong Experience in Data Architecture, specifically with Databricks Architecture. Expert in Databricks Lakehouse (Delta Lake, Unity Catalog, MLflow), AWS, Snowflake, and Apache Iceberg. Strong MLOps & CI/CD Expertise Proficient in Python/Scala (Spark) for data governance, security, and enterprise data platform design. Databricks certifications and GenAI architecture experience preferred. Key Responsibilities: Architect and strategize Databricks on AWS/Snowflake integration for secure, scalable data/AI platforms. Architect seamless Snowflake/Databricks data flow via Apache Iceberg (including ML output). Design cost-managed multi-region Databricks MLOps platform and data flows. Implement Unity Catalog for fine-grained access control and secure team coexistence with Workspaces. Develop Databricks-native MLOps (environment parity, Git-driven CI/CD, governed access, MLflow governance, standardized deployment, monitoring). Define enterprise-scalable AI governance for GenAI production deployment. Benefits This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility. Originally posted on Himalayas

Point C is a National third-party administrator (TPA) with local market presence that delivers customized self-funded benefit programs. Our commitment and partnership means thinking beyond the typical solutions in the market – to do more for clients – and take them beyond the standard “Point A to Point B.” We have researched the most effective cost containment strategies and are driving down the cost of plans with innovative solutions such as, network and payment integrity, pharmacy benefits and care management. There are many companies with a mission. We are a mission with a company. We're looking for a Databricks Architect & Developer to design and build enterprise-scale data platforms supporting multiple claims systems. This role will own the end-to-end lakehouse architecture — from ingestion through governance — while partnering closely with data engineers, analysts, and business stakeholders to translate requirements into robust, production-ready technical solutions on Azure. Primary Responsibilities: Design and implement scalable data platforms using Databricks, Apache Spark, Delta Lake, and SQL, producing solution architecture and technical design documentation. Develop Medallion Architecture (Bronze, Silver, Gold) for enterprise data workloads from multiple claim systems (VBA, Quicklink, HealthPac, and file-based TPAs). Build and optimize production-grade ETL/ELT pipelines using Databricks Workflows, PySpark, and SQL. Work with ADF+ADLS ingest and existing kill-and-fill dimension patterns. Design and maintain data models and Delta tables, implementing schema evolution, time travel, partitioning, and optimization. Design solutions on Azure, integrating cloud storage and databases. Implement Unity Catalog, access controls, data governance, lineage, and security. Translate claim-system data dictionaries into Unity Catalog tables for reporting and APIs. Define and execute performance and cost-optimization strategies across the platform. Work with data engineers, analysts, and business stakeholders to translate requirements into technical designs. Establish CI/CD practices for Databricks notebooks, jobs, and infrastructure. Troubleshoot production data pipelines and support platform reliability. Qualifications: Required 5–7 years of data engineering/cloud experience. Strong hands-on experience with Databricks and Apache Spark. Advanced PySpark and SQL. Strong understanding of Delta Lake and Medallion Architecture. Experience with at least one cloud platform: Azure. Knowledge of Data Governance, Unity Catalog, IAM/RBAC, and security. Experience with Git, CI/CD, and infrastructure-as-code concepts. Strong understanding of data warehousing, dimensional modeling, and distributed data processing. Preferred Azure Data Factory Terraform Kafka or other streaming technologies Power BI platforms Databricks certifications Experience designing enterprise data lakes/lakehouses Individual compensation will be commensurate with the candidate's experience and qualifications. Certain roles may be eligible for additional compensation, including bonuses, and merit increases. Additionally, certain roles have the opportunity to receive sales commissions that are based on the terms of the sales commission plan applicable to the role. Pay Transparency $100,000 — $120,000 USD Benefits: Comprehensive medical, dental, vision, and life insurance coverage 401(k) retirement plan with employer match Health Savings Account (HSA) & Flexible Spending Accounts (FSAs) Paid time off (PTO) and disability leave Employee Assistance Program (EAP) Equal Employment Opportunity : At Point C Health, we know we are better together. We value, respect, and protect the uniqueness each of us brings. Innovation flourishes by including all voices and makes our business—and our society—stronger. Point C Health is an equal opportunity employer and we are committed to providing equal opportunity in all of our employment practices, including selection, hiring, performance management, promotion, transfer, compensation, benefits, education, training, social, and recreational activities to all persons regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, genetic information, pregnancy, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, and military and veteran status, or any other protected status protected by local, state or federal law.

Databricks Architect

C2S Technologies Inc

San Francisco, CA

No Description

Senior Databricks Architect

Stitch Consulting Services, Inc.

United States

Stitch is the global leader in helping brands drive CRM performance through Braze and Databricks. We work with Fortune 1000 brands to design and execute martech-driven solutions and lifecycle marketing strategies that drive meaningful outcomes. Our fast-growing team spans the US, UK, and Canada. We’re actively building the best customer relationship marketing (CRM) consultancy in the world. Not the biggest—the best. We’re looking for teammates who are energized by this challenge. A note before you apply: We're not actively hiring for this role today, but we're building relationships ahead of upcoming client work. If your background fits, we'd like to start a conversation now so we're ready to move when a project lands! Who You Are First and foremost, you’re motivated by impact. To be the best CRM consultancy in the world, we have to be motivated by performance—both in how our work drives outcomes for our customers, and for how our work drives outcomes for Stitch. This means you’re not content with the status quo. You’re always looking towards what’s next and seeking opportunities to grow yourself, grow our customers, and grow Stitch. You have relentless standards and uphold them unapologetically. You move nimbly, take ownership, drive things forward, and make the people around you better. If this sounds like you, you will thrive here. The Role As a Senior Databricks Architect, you'll play a pivotal role in delivering custom, enterprise-grade solutions that sit at the intersection of Databricks and Braze. You'll own end-to-end Lakehouse architecture and work directly with enterprise clients to design and build what makes Braze really sing: sharper data foundations, smarter segmentation, and AI-driven customer 360 solutions that wouldn't be possible without the right infrastructure underneath. You'll combine deep technical expertise with the agility of a high-growth consultancy—hands-on in the platform in the morning, leading an architecture conversation with a CMO in the afternoon. To thrive in this role, you'll need to be as comfortable writing PySpark as you are presenting recommendations to a marketing or data engineering team. You bring a strong point of view, a curiosity-first approach to client problems, and the drive to build something at Stitch that didn't exist before you got here. What You’ll Do Lead and drive client working sessions focused on data architecture and data mapping, bringing clarity and direction to complex discussions with senior stakeholders. Design and own end-to-end Databricks Lakehouse architecture for marketing data ingestion, transformation, storage, and consumption—leveraging Unity Catalog, Delta Lake, Delta Live Tables, and Databricks SQL Warehouse. Design integrations between Databricks and martech platforms (Braze, CDPs, ect) to enable customer 360 views, churn prediction, media mix modeling, dynamic pricing, and lifetime value analysis. Design and implement robust data models—including medallion architecture, Star Schema, and Data Vault—optimized for marketing analytics workloads. Enable marketers to query data conversationally and generate actionable insights without SQL through Databricks Genie and AI-powered analytics. Support the design and implementation of AI agents using Agent Bricks and the Mosaic AI Agent Framework. Review and interpret technical capability maps and frameworks, connecting them to data architecture and design decisions. Architect data governance, security, and access control policies using Unity Catalog, including lineage tracking, audit logging, PII masking, and marketing data privacy compliance. Integrate Databricks workflows into CI/CD pipelines using Terraform, Git, and Azure DevOps; implement infrastructure-as-code and automated deployment for notebooks, jobs, and clusters. Partner with clients on roadmaps, POCs, and migrations; support pre-sales efforts with technical proposals, whiteboarding sessions, and project estimation. Manage your time to meet billable targets of 36+ hours per week. Travel up to 20% for client meetings, workshops, and onsite engagements. How You Consult At Stitch, every role is expected to operate as a trusted advisor whose expertise helps our clients with their business needs. As a Databricks Architect, your credibility comes from deep technical depth combined with the ability to communicate clearly across technical and business audiences. Lead requirements, validation, and ideation sessions with technical and business stakeholders. Advise clients on data architecture and platform tradeoffs. Navigate ambiguity and translate between marketers and engineers. Build relationships with client technical leads. Become the architect they trust and request. Bring a strong point of view and recommendations—not just options. Anticipate what the client needs before they ask. Own outcomes on your technical workstream. Lead without being asked. Share feedback with peers regularly that makes all of us better. What Success Looks Like Clients see you as a trusted data architecture advisor. You’re confident meeting with senior stakeholders and bringing a strong point of view around best practices and creative solutions. You show up to every meeting prepared and engaged. Every touchpoint—Slack, email, Zoom, or onsite—is an opportunity to add value. You’re responsive and work with a sense of urgency. You consistently meet deadlines. We’re a professional services business, so our success depends on client satisfaction. Hitting your deadlines gives the Stitchers depending on your work enough runway to do theirs. You manage your weekly schedule intentionally to meet quarterly billable targets. You’ll be context-switching between deep technical work, client meetings, internal collaboration, certifications, and time-tracking—oftentimes across multiple clients at once. Staying organized is what makes it all feel manageable. Who Your Team Will Be Stitchers come with diverse backgrounds and experiences—but we are tied together by our Common Threads. These are the values that define our Stitchers: Form Lasting Bonds — We’re a people business. We consistently show up for our team, our partners, and our clients in ways that build trust and champion others. Seek Solutions — We aren’t order takers. We’re solution designers. We solve problems, move fast, deliver excellence, and drive results. We always have a point of view. Don’t Settle — We don’t accept the way things have always been done. We think bigger, pursue growth, and find motivation in the discomfort that scares most people away. Take the Lead — We forge our own path without waiting for permission. We push boundaries, lead our team and customers, and find the answer when one doesn’t exist yet. What You’ll Get at Stitch The opportunity to work within multiple Fortune 1000 brands across the retail, media, gaming, quick-service, financial services, travel, and healthcare industries. Working alongside the most concentrated group of Braze experts in the world—backed by more Braze credentials and experience than any other company across the globe. The ability to feel your impact and shape how Stitch grows as we continue to scale through hypergrowth. The chance to learn new technologies (like Braze, Databricks, and AI) and grow faster than you ever have before. Of course, we offer competitive compensation, benefits, and growth opportunities, too. Requirements 5+ years of experience in data engineering or data architecture. 3+ years of hands-on Databricks experience, including PySpark, SQL, and Scala. Proven experience integrating Databricks with Braze or similar martech platforms for marketing analytics (Salesforce Marketing Cloud, Responsys, Adobe). Deep expertise in Delta Lake, Unity Catalog, Delta Live Tables, structured streaming, and MLflow. Strong data modeling skills across medallion architecture, Star Schema, and Data Vault. Cloud platform experience across AWS, Azure, or GCP, with proficiency in IaC tooling such as Terraform and ARM templates. Track record of leading and mentoring engineering teams in consulting environments. Client-facing experience within an agency or consultancy required. Must be eligible to work in the United States or Canada without visa sponsorship, now or in the future. Benefits Medical, dental, vision, and life insurance 401k with company match Flexible PTO policy Monthly tech stipend Paid parental leave In-person onboarding experience at our HQ in Indianapolis, Indiana Mental well-being support Originally posted on Himalayas

: Azure Databricks Architect

TechSpace Solutions Inc.

Charlotte, NC

Job Title: Azure Databricks Architect Location: Charlotte, NC (Day1 Onsite) Job Summary: We are seeking a highly skilled and motivated Technical Team Lead with extensive experience in Azure Databricks to join our dynamic team. The ideal candidate will possess a strong technical background, exceptional leadership abilities, and a passion for driving innovative solutions. As a Technical Team Lead, you will be responsible for guiding a team of developers and engineers in the design, development, and implementation of data driven solutions that leverage Azure Databricks. Responsibilities: Lead and mentor a team of technical professionals, fostering a collaborative and high performance culture. Design and implement data processing solutions using Azure Databricks, ensuring scalability and efficiency. Collaborate with cross functional teams to gather requirements and translate them into technical specifications. Oversee the development lifecycle, from planning and design to deployment and maintenance. Conduct code reviews and provide constructive feedback to team members to ensure code quality and adherence to best practices. Stay up to date with industry trends and emerging technologies related to Azure Databricks and data engineering. Facilitate communication between technical and non technical stakeholders to ensure alignment on project goals. Identify and mitigate risks associated with project delivery and team performance. Mandatory Skills: Proven expertise in Azure Databricks, including experience with Spark, data pipelines, and data lakes. Strong programming skills in languages such as Python, Scala, or SQL. Experience with cloud based data storage solutions, particularly Azure Data Lake Storage and Azure SQL Database. Solid understanding of data modeling, ETL processes, and data warehousing concepts. Demonstrated ability to lead technical teams and manage multiple projects simultaneously. Preferred Skills: Familiarity with Azure DevOps for CI/CD processes. Experience with machine learning frameworks and libraries. Knowledge of data governance and compliance standards. Strong analytical and problem solving skills. Excellent communication and interpersonal skills. Qualifications: Bachelor`s degree in Computer Science, Information Technology, or a related field. 7 10 years of experience in data engineering, software development, or a related technical role. Proven track record of leading technical teams and delivering successful projects. Relevant certifications in Azure or data engineering are a plus.

Resident Solution Architect (Databricks)

Jupiter IT Solutions LLC

San Francisco, CA

Job Summary: We are seeking a Senior Solution Architect to join our Databricks Practice and play a pivotal role in shaping data modernization journeys for enterprise customers. This is a customer-facing, consulting-oriented role where you will engage with CDOs, Data Architects, and Engineering leaders to design and deliver scalable, future-ready Lakehouse solutions on the Databricks Data Intelligence Platform. You will be the trusted technical advisor — translating business problems into architectural blueprints, guiding customers through EDW modernization programs, and championing the adoption of Databricks` most advanced capabilities including Lakeflow Declarative Pipelines (LDP), Lakeflow Connect, Serverless Compute, Unity Catalog, and AI/BI workloads. Responsibilities: Lead pre-sales and delivery architecture conversations with enterprise customers, owning the technical narrative from discovery through solution design and through implementation oversight. Design end-to-end Databricks Lakehouse architectures spanning ingestion, transformation, governance, ML, and consumption layers — aligned to Medallion Architecture principles. Drive EDW modernization engagements, including migration strategies from legacy platforms (Teradata, Netezza, Oracle, SAS, Greenplum, Synapse, Snowflake, on-prem Hadoop) to Databricks, with clear wave planning, risk mitigation, and TCO/ROI articulation. Advise customers on the adoption of advanced Databricks features. Lakeflow Declarative Pipelines (LDP / formerly DLT) for production-grade ETL with built-in data quality and lineage. Lakeflow Connect for managed ingestion from SaaS, databases, and file sources. Serverless Compute (SQL warehouses, jobs, notebooks) for cost and operational efficiency. Unity Catalog for unified governance, lineage, and fine-grained access control. Databricks Asset Bundles (DAB) for CI/CD and environment promotion Databricks SQL, AI/BI Dashboards, Genie for self-service analytics Expertise in Data Bulid Tool (DBT) and Databricks Autoloader Databricks SQL, AI/BI Dashboards, Genie for self-service analytics MLflow, Model Serving, and Mosaic AI for ML and GenAI workloads Conduct architecture deep-dives, PoCs, and workshops — including cost modelling roadmaps, runbooks and executive presentations. Produce Client ready deliverables. HLD / LLD documents, reference architecture, migration road maps, runbook and execution presentations Partner with sales, delivery, and Databricks field teams to shape proposals, SoWs, and bid responses. Stay ahead of the Databricks product roadmap and evangelize new capabilities internally and with customers. Mentor data engineers, platform engineers, and junior architects on Databricks best practices. Qualifications 8+ years in data engineering / data platform architecture, with 3+ years handson on Databricks in a customer-facing or consulting capacity. Demonstrated experience leading at least 2–3 large- scale EDW modernization or Lakehouse migration programs end to end. Strong, fundamentals-level understanding of the Databricks Data Intelligence Platform. Delta Lake internals (transaction log, OPTIMIZE, Z- order, Liquid Clustering, Deletion Vector, Predictive Optimization) Spark execution model, Photon, cluster sizing, and performance tuning. Unity Catalog object model (metastore, catalogs, schemas, volumes, external locations, stor age credentials). Workspace, account, and identity architecture across AWS / Azure / Google Cloud Platform. Handson experience designing and deploying Lakeflow Declarative Pipelines, Lakeflow Conn ect, and Serverless workloads in production. Solid grounding in Medallion Architecture, dimensional modeling, and data governance fra meworks. Strong SQL and PySpark skills; comfort reading and reasoning about Spark execution plans. Cloud fluency on at least one of Azure, AWS, or Google Cloud Platform including networking, IAM, and storage layers (ADLS Gen2 / S3 / GCS). Excellent communication and stakeholder management skills able to engage equally with engineers and C- suite. Willing to travel and stay overseas for Solutioning and Delivering projects. Required Skills Databricks certifications: Certified Data Engineer Professional, Certified Machine Learning Pr ofessional, or Databricks Certified Solutions Architect Professional. Experience with DR architectures (Delta Deep Clone, crossregion replication, RPO/RTO design). Exposure to MLOps / GenAI patterns on Databricks (MLflow, Model Serving, Vector Search, Mosaic AI Agent Framework) Familiarity with legacy ETL/ELT platforms (Informatica, ODI, SAS DI, DataStage, Talend) for migration credibility. Experience with Terraform / Databricks Asset Bundles for IaC and CI/CD. Working knowledge of Immuta, Collibra, Purview, or Alation for governance integration. Industry depth in BFSI, Insurance, Retail, Manufacturing, or Healthcare. Preferred Skills Owned the architecture for at least 2 strategic customer engagements from discovery to golive. Established yourself as the goto advisor on advanced Databricks adoption (LDP, Lakeflow Co nnect, Serverless) within the practice Contributed to reusable accelerators, reference architectures, and migration playbooks that scale across the practice. Built strong working relationships with Databricks field teams and contributed to joint p ursuits.

Principal Architect - Databricks

SHI International Corp.

United States

About Us Since 1989, SHI International Corp. has helped organizations change the world through technology. We’ve grown every year since, and today we’re proud to be a $16 billion global provider of IT solutions and services. Over 17,000 organizations worldwide rely on SHI’s concierge approach to help them solve what’s next. But the heartbeat of SHI is our employees – all 7,000 of them. If you join our team, you’ll enjoy: Our commitment to diversity, as the largest minority- and woman-owned enterprise in the U.S. Continuous professional growth and leadership opportunities. Health, wellness, and financial benefits to offer peace of mind to you and your family. World-class facilities and the technology you need to thrive – in our offices or yours. Job Summary We are expanding our Databricks capability within the Data and AI practice and are looking for a Principal Solutions Architect to lead the technical side of it. You will work directly with customers from the outset, qualifying opportunities, conducting technical discovery with customer architects and data leaders, designing target-state platforms, and owning the technical win. Much of the work ahead involves platform build-out, migration, and consolidation, helping enterprises move to the Databricks Lakehouse from Hadoop and Spark estates, legacy analytics platforms, established data warehouse and appliance environments, and other cloud platforms. The role also supports AI and machine learning initiatives that Databricks is designed to enable. This is a senior individual contributor position with significant influence over the solutions we build and bring to market. It is ideal for someone who wants to shape a capability rather than operate within one that is already defined. Role Description Own the Technical Side of Databricks Pursuits Lead qualification, technical discovery, target architecture design, effort estimation, and risk assessment. Develop technical content for proposals and Statements of Work (SOWs). Build and maintain technical relationships with customer architects and stakeholders. Provide customers with realistic and accurate assessments of migration complexity, implementation effort, AI workload readiness, and associated risks. Provide Architectural Oversight Through Delivery Review architecture decisions throughout project delivery. Confirm that the delivered solution aligns with what was originally scoped and proposed. Surface technical risks and issues early in the engagement. Remain closely involved throughout delivery to ensure accountability for architecture and outcomes. Shape Databricks Service Offerings Define the technical content of market-facing Databricks offerings. Establish what is included in scope, how success is measured, and what evidence validates successful completion. Create repeatable delivery standards and frameworks that teams can execute consistently. Partner with Databricks Engage directly with Databricks field teams and specialist architects on joint customer accounts. Build productive relationships with Databricks technical teams. Effectively collaborate and navigate technical challenges, feedback, and differing viewpoints from vendor architects and specialists. Behaviors and Competencies Willingness to Learn: Can apply new learning to daily work, encourage and facilitate learning in others, and actively make changes to work based on feedback. Self-Development: Can demonstrate a commitment to continuous learning and adaptability to new ideas and methods. Leadership: Can take ownership of complex team initiatives, collaborate with others in decision-making processes, and drive team performance. Strategic Thinking: Can analyze complex situations, anticipate future trends, and align and integrate strategies across departments or functions. Problem-Solving: Can proactively identify and take ownership of complex problem-solving initiatives, initiate preventative measures, collaborate with others to find solutions, and drive successful outcomes. Analytical Thinking: Can use advanced analytical techniques to solve complex problems, draw insights, and communicate the solutions effectively. Prioritization: Can take ownership of complex task management, collaborate with others to align priorities, and drive team efficiency. Customer-Centric Mindset: Can take ownership of customer-centric initiatives, ensuring products and services align with customer needs. Collaborates with cross-functional teams to integrate customer feedback into product development. Organization: Can oversee complex projects with multiple moving parts, ensure team alignment with organizational systems, and adapt to changing priorities. Communication: Can effectively communicate complex ideas and information to diverse audiences, facilitate effective communication between others, and mentor others in effective communication. Interpersonal Skills: Can communicate effectively, build relationships, resolve conflicts, influence others, and support others in developing their interpersonal skills in major situations. Skill Level Requirements Lakehouse Platform and Architecture Account and workspace design Unity Catalog and metastore architecture Compute strategy across interactive, jobs, and serverless workloads Open table format decisions Cost architecture and design choices that affect long-term scalability and affordability The ability to design platforms that remain technically and financially sustainable at enterprise scale is critical. Migration and Consolidation Migrating organizations from Hadoop and Spark environments Modernizing legacy analytics and statistical platforms Consolidating established warehouses and appliance-based solutions Migrating workloads from other cloud platforms Key areas of expertise include: Platform assessments Wave planning and migration strategy Workload and code conversion Reconciliation and parity validation Cutover planning and execution This is expected to represent a significant portion of the work within the practice and requires genuine expertise rather than general familiarity. Data Engineering and Pipelines Batch data ingestion Streaming data ingestion Declarative pipeline development Workflow orchestration Testing and validation frameworks Data quality instrumentation Building and operating reliable, production-ready data engineering solutions Machine Learning and AI Engineering Feature engineering Experiment tracking Model registry and serving Evaluation and validation frameworks Retrieval and grounding architectures Agent development This represents one of Databricks’ key differentiators and is an area where many customers require assistance moving from proof-of-concept solutions to production-grade, supportable implementations. Governance at the Perimeter Catalog-based access controls Data classification Data masking Data lineage and governance frameworks Candidates should understand how Databricks governance integrates with enterprise governance strategies and be able to address challenges that exist across organizational and platform boundaries. Consumption Economics Compute sizing strategies Workload placement optimization Serverless versus classic compute trade-offs Consumption attribution and chargeback models Cost management and optimization practices Candidates must be comfortable discussing platform costs with customers and providing practical guidance on controlling and forecasting consumption. Technical Depth Expectations Candidates do not need to be equally strong across all six areas; however, they must possess: Deep expertise in lakehouse architecture and platform design Deep expertise in migration and consolidation Deep expertise in data engineering Sufficient proficiency in the remaining areas to recognize when specialist support should be engaged Other Requirements Databricks Expertise Substantial hands-on Databricks experience gained through: A Databricks partner organization Databricks directly Managing a significant Databricks Lakehouse environment internally This role requires Databricks-specific expertise rather than general data platform leadership experience. Enterprise Migration and Consolidation Experience Proven success delivering enterprise-scale migration and consolidation initiatives. Ability to discuss at least one major migration project in detail, including lessons learned and outcomes. Production Machine Learning and AI Experience Experience operating and supporting production machine learning or AI solutions. Expertise beyond proof-of-concept implementations. Demonstrated understanding of the operational, governance, and maintenance considerations required for production AI workloads. Principal-Level Technical Leadership Proven success operating at Principal Architect level or equivalent. Recognized as the senior technical authority in customer engagements. Trusted to commit organizations to scopes, architectures, and technical approaches. Presales Experience Experience in presales environments, or Delivery leadership experience demonstrating the ability to: Lead customer discussions Define scope and solution approaches Develop proposals and Statements of Work Stand behind technical commitments made during the sales process Vendor Collaboration Comfortable working with and being challenged by vendor architects and technical specialists. Certifications Databricks certification preferred. Ability to obtain certification quickly if not currently certified. Certification support and funding are provided. The estimated annual pay range for this position is $195,000 - $250,000 which includes a base salary and bonus. The compensation for this position is dependent on job-related knowledge, skills, experience, and market location and, therefore, will vary from individual to individual. Benefits may include, but are not limited to, medical, vision, dental, 401K, and flexible spending. Equal Employment Opportunity – M/F/Disability/Protected Veteran Status Originally posted on Himalayas

Principal Observability Architect (Splunk & Databricks)

Scicom Infrastructure Services, Inc.

United States

Position Summary We are seeking a highly experienced Principal Observability Architect to lead the design, implementation, modernization, and optimization of enterprise-scale observability and analytics platforms. This role will serve as the technical authority for log management, observability engineering, telemetry pipelines, AIOps, security analytics, and data lakehouse architectures leveraging Splunk, Databricks, Cribl, OpenTelemetry, and cloud-native technologies. The ideal candidate possesses deep expertise in traditional observability platforms (Splunk, Dynatrace, AppDynamics, ServiceNow ITOM) and modern data lakehouse architectures utilizing Databricks, Delta Lake, Unity Catalog, and AI/ML-driven analytics. This individual will drive the strategic transformation from legacy SIEM and observability platforms toward scalable, cloud-native observability data lakes. Key Responsibilities Enterprise Architecture & Strategy Define enterprise observability architecture standards, patterns, and roadmaps. Lead observability transformation initiatives involving Splunk modernization and Databricks adoption. Develop reference architectures for telemetry ingestion, storage, analytics, security, and AI-driven operations. Align observability strategies with business, security, compliance, and operational objectives. Create executive-level architecture presentations, business cases, and technology roadmaps. Splunk Platform Leadership Architect large-scale Splunk Enterprise and Splunk Cloud environments. Design and optimize: Indexer clusters Search head clusters Forwarder architectures Deployment servers Data models ITSI implementations Define ingestion, retention, indexing, and data lifecycle strategies. Lead migration initiatives involving: Splunk to Databricks Heavy Forwarders to Cribl SIEM modernization programs Optimize SPL searches, data models, summary indexing, and dashboard performance. Databricks & Lakehouse Architecture Architect enterprise observability data lake solutions using: Databricks Lakehouse Delta Lake Unity Catalog Delta Live Tables Structured Streaming Mosaic AI Genie Design Medallion Architectures: Bronze Silver Gold Develop governance strategies including: RBAC Data masking Data lineage Audit controls Create high-performance log analytics solutions capable of supporting petabyte-scale telemetry environments. Enable self-service analytics and AI-powered observability use cases. Telemetry & Data Engineering Design ingestion architectures supporting: OpenTelemetry OCSF Syslog Kafka Azure Event Hubs AWS Kinesis GCP Pub/Sub Cribl Define normalization and enrichment frameworks. Establish data quality and schema management processes. Design real-time and batch processing pipelines. AIOps & Advanced Analytics Lead implementation of: AIOps Predictive analytics Root cause analysis Anomaly detection Event correlation Integrate observability datasets with AI/ML platforms. Develop observability use cases leveraging: Mosaic AI Agentic AI LLMs Generative AI Build operational intelligence and executive KPI dashboards. Security & Compliance Architect observability solutions supporting: SOC operations Threat hunting Security analytics Compliance reporting Design frameworks aligned with: HIPAA PCI-DSS SOX NIST ISO 27001 Implement data governance and security controls across observability platforms. Leadership & Governance Provide technical leadership to engineering teams. Mentor architects, engineers, and developers. Conduct architecture reviews and design governance. Define platform standards, best practices, and operational procedures. Engage directly with executive stakeholders and business leaders. Required Qualifications Experience 10+ years of experience in Enterprise Observability, Monitoring, or Security Analytics. 5+ years architecting large-scale Splunk environments. 3+ years designing Databricks Lakehouse architectures. Experience managing environments exceeding: 50 TB/day preferred 100+ TB/day strongly preferred Experience leading enterprise transformation programs. Splunk Expertise Deep expertise in: Splunk Enterprise Splunk Cloud Splunk ITSI Enterprise Security SPL Development Data Models Indexer Clustering Search Head Clustering SmartStore Heavy Forwarders Universal Forwarders Databricks Expertise Strong experience with: Databricks Lakehouse Delta Lake Unity Catalog Delta Live Tables Structured Streaming Databricks SQL Genie Mosaic AI Lakehouse Federation Cloud Platforms Experience with one or more: Microsoft Azure Amazon Web Services Google Cloud Data Technologies Strong knowledge of: Kafka OpenTelemetry OCSF Iceberg Spark SQL Python REST APIs Event Streaming Architectures Preferred Qualifications Experience with Cribl Stream and Cribl Edge Experience with Dynatrace, AppDynamics, Datadog, or New Relic Experience with ServiceNow ITOM/Event Management Experience designing AI/ML operational analytics solutions Experience with Security Data Lakes and SIEM modernization initiatives Experience with FinOps and cloud cost optimization Experience building observability platforms for healthcare, financial services, retail, or large enterprise organizations Certifications (Preferred) Splunk Splunk Enterprise Certified Architect Splunk Core Certified Consultant Databricks Databricks Certified Data Engineer Professional Databricks Certified Solutions Architect Cloud Azure Solutions Architect Expert AWS Solutions Architect Professional Google Professional Cloud Architect Success Metrics Within the first 12 months, the architect will: Deliver enterprise observability architecture roadmap. Reduce observability platform costs through modernization initiatives. Design and implement a scalable observability data lake architecture. Improve telemetry ingestion performance and reliability. Enable AI-powered analytics and operational intelligence capabilities. Establish enterprise governance standards for observability and security telemetry. Support petabyte-scale observability and security analytics workloads. Ideal Background Candidates from organizations utilizing large-scale observability environments such as healthcare, banking, retail, telecommunications, logistics, cloud providers, or managed services organizations are highly desirable. Experience supporting environments generating 100TB+ of telemetry per day and integrating Splunk, Databricks, Cribl, OpenTelemetry, and cloud-native data platforms is strongly preferred. Originally posted on Himalayas

Databricks Solutions Architect, Pre-Sales Aimpoint Digital is a market-leading data, AI, and analytics consulting firm. We help organizations design, build, and operationalize modern data platforms, analytics solutions, and production AI applications. As a leading Databricks partner, we are expanding our pre-sales solutions organization and are seeking a Databricks Solutions Architect, Pre-Sales to help shape and win complex Databricks consulting engagements. About the Role As a Databricks Solutions Architect, Pre-Sales, you will own the technical portion of the sales cycle end-to-end for Databricks opportunities, from initial discovery through solution design, scoping, proposal development, technical validation, and handoff to delivery. You will partner with sales, alliance, and delivery teams to understand client needs, design the right technical solution, and translate that solution into a credible and executable consulting engagement. This role is designed for someone who has done similar work in a consulting or professional services environment. You know how to move from an ambiguous client problem to a clear architecture, delivery approach, team structure, estimate, and statement of work. You will work across platform implementations, migrations, lakehouse architecture, data engineering, semantic layers, analytics, and AI use cases. Your technical depth should be strongest in data and platform engineering, with a strong understanding of how modern data architectures support downstream analytics and AI. What You Will Do Own the technical portion of Databricks pursuits from first client conversation through signed engagement and transition to delivery. Lead technical discovery with client engineering, architecture, data, analytics, AI, and executive stakeholders. Design architectures for new Databricks platforms, migrations, modernization programs, and complex data workloads. Define lakehouse and medallion architectures across bronze, silver, gold, and downstream consumption layers. Solution data ingestion, transformation, orchestration, governance, security, and semantic layer patterns. Design data foundations that support BI, self-service analytics, Genie, ML, GenAI, RAG, and agentic AI use cases. Translate technical requirements into project scope, delivery phases, assumptions, risks, resource plans, and estimates. Partner with sales and delivery leaders to develop proposals and statements of work. Build and deliver technical demos, proofs of concept, architecture workshops, and solution presentations that help clients understand and validate the proposed approach. Create reusable pre-sales materials, including demo environments, reference architectures, discovery frameworks, solution patterns, technical content, and estimation models. Work directly with Databricks account teams and solution architects on joint pursuits and co-sell opportunities. Ensure clean handoffs from pre-sales into delivery so project teams inherit clear architecture, scope, assumptions, and client context. Who We Are Looking For We are looking for a strong consulting technologist who combines technical depth, client presence, and commercial judgment. You have likely worked in a consulting, systems integrator, or professional services organization where you owned or played a major role in complex data platform pursuits. You are comfortable entering a sales cycle early, leading discovery, challenging assumptions, whiteboarding architecture, building demos, estimating delivery effort, and helping turn a technical solution into a signed engagement. You have enough hands-on engineering experience to earn credibility with technical teams, while being able to simplify complex concepts for data leaders and executives. You understand that strong pre-sales work is not about designing the most sophisticated architecture. It is about identifying the right solution, demonstrating that it will work, building client confidence, and creating an engagement that the delivery team can execute successfully. Qualifications 7+ years of experience in data engineering, platform engineering, solution architecture, technical consulting, or related roles. Significant experience in consulting, professional services, systems integration, or technical pre-sales. Demonstrated experience owning the technical workstream of complex enterprise sales cycles. Strong Databricks architecture and implementation experience in enterprise environments. Deep knowledge of modern data engineering, including Spark, SQL, Python, data pipelines, orchestration, data modeling, and distributed processing. Strong understanding of lakehouse architecture, medallion patterns, Unity Catalog, Delta Lake, governance, and security. Experience with data platform or warehouse migrations. Understanding of semantic layers, analytics architectures, and how enterprise data platforms support AI and ML workloads. Experience leading client discovery, architecture workshops, solution design, demos, estimation, and SOW scoping. Strong client-facing communication skills across engineers, architects, data leaders, and executives. Databricks certifications preferred. Location This is a full-time, remote role within the United States, with travel to client sites and partner events as needed. Priority evaluation provided for candidates based in New York City, Chicago, and Houston/Dallas. Atlanta-based applicants will have the opportunity to work in our headquarters in Sandy Springs, GA.

Databricks Engineer / Architect

Celer Soft LLC

Jersey City, NJ

Position: Databricks Engineer / Architect Employment Type: Contractual Work Arrangement: Remote Experience: 10+ years overall, with 4+ years of hands-on Databricks experience Location: Remote About the Role We are seeking an experienced Databricks Engineer / Architect to design, develop, and optimize modern data platforms and large-scale data engineering solutions using Databricks and cloud technologies. The ideal candidate will have strong hands-on expertise in Databricks, Apache Spark, Python/SQL, Delta Lake, data architecture, ETL/ELT pipelines, and cloud platforms. This role requires someone who can operate at both the engineering and architecture levels translating business requirements into scalable, secure, and high-performance data solutions. Key Responsibilities Design and architect scalable, reliable, and high-performance data platforms using Databricks. Develop and optimize data pipelines using PySpark, Python, SQL, Spark, and Delta Lake. Design modern Lakehouse architectures and implement enterprise-grade data solutions. Develop batch and streaming data pipelines and integrate data from multiple sources. Implement Delta Lake capabilities including schema evolution, partitioning, optimization, and data lifecycle management. Work with Databricks Workflows, Jobs, notebooks, clusters, and related platform capabilities. Design and implement data ingestion, transformation, and orchestration frameworks. Optimize Spark workloads, Databricks clusters, SQL queries, and data pipelines for performance and cost. Establish and implement data engineering best practices, coding standards, CI/CD, and deployment processes. Implement appropriate security, governance, access controls, and data quality mechanisms. Collaborate with data scientists, analysts, application teams, cloud engineers, and business stakeholders. Provide technical leadership and mentorship to data engineering teams. Evaluate existing data architectures and recommend improvements, modernization strategies, and technology adoption. Troubleshoot complex production issues and provide root-cause analysis and long-term solutions. Participate in architecture reviews, technical design sessions, and documentation of enterprise data solutions. Required Technical Skills Databricks & Data Engineering Strong hands-on experience with Databricks Advanced knowledge of Apache Spark / PySpark Strong proficiency in Python and SQL Extensive experience with Delta Lake Experience designing and implementing scalable ETL/ELT pipelines Strong understanding of Lakehouse architecture and modern data platforms Experience with batch and real-time/streaming data processing Cloud Technologies Strong experience with at least one major cloud platform: Microsoft Azure - Azure Data Lake Storage, Azure Data Factory, Azure Synapse, Azure Key Vault, Azure DevOps AWS - S3, Glue, Lambda, IAM, Redshift, CloudWatch Google Cloud Platform - Cloud Storage, BigQuery, Dataflow, Pub/Sub, IAM Preferred Qualifications Databricks certifications such as Databricks Certified Data Engineer or Databricks Certified Data Engineer Professional Experience with Unity Catalog and Databricks governance capabilities Experience implementing enterprise Medallion Architecture (Bronze/Silver/Gold) Experience with structured streaming and event-driven architectures Knowledge of data modeling and dimensional modeling Experience with Kafka or other messaging/streaming platforms Experience with data quality frameworks and observability Familiarity with MLOps and integration with machine learning platforms Strong communication, documentation, and stakeholder-management skills Education Bachelor`s or Master`s degree in Computer Science, Information Technology, Engineering, or a related field. Equivalent professional experience may be considered. What We re Looking For The successful candidate should be: A strong hands-on Databricks Engineer who can also think at the architecture level. Comfortable working independently in a fully remote environment. Capable of translating complex business requirements into scalable technical solutions. Strong in problem-solving, troubleshooting, and performance optimization. An effective communicator who can work with both technical and non-technical stakeholders. Comfortable providing technical leadership and driving architecture decisions.

Databricks Solution Architect

Bits In Glass

United States

Databricks Solution Architect Bits In Glass • Remote-friendly (Canada) Bits In Glass (BIG) is a high-growth AI and automation consulting firm with offices across Canada, the United States, India, and the United Kingdom. Our portfolio spans more than 10 leading technologies across AI, cloud, data, automation, and business applications. Recognized globally as a Great Place to Work and the recipient of multiple partner excellence awards, BIG is built on collaboration, innovation, and delivering measurable business outcomes for enterprise clients. We are a team of experienced technology professionals who enjoy solving complex challenges, celebrating wins together, and helping customers modernize with confidence. About the Role We are looking for a hands-on Databricks Solution Architect to design the data and AI platforms that power our enterprise clients. This is a deeply technical role for an architect who wants to stay close to the technology — shaping Lakehouse architectures, building working prototypes, and setting the technical direction that delivery teams carry forward. You will work directly with prospects and customers to understand their data challenges and design solutions on the Databricks Lakehouse Platform that actually fit their environment. That means partnering with our account and delivery teams throughout the sales process, ensuring the architecture you propose gets built. This role is ideal for someone who enjoys solving hard data problems, solution storytelling, and being the trusted technical voice customers rely on. What You'll Do Design scalable Databricks solution architectures — Lakehouse, Delta Lake, and Unity Catalog patterns - tailored to each customer's environment and business goals. Lead technical discovery workshops to understand customer business objectives, data challenges, and current-state architecture Build working prototypes, proofs-of-concept, and reference architectures that showcase the capabilities of the Databricks Lakehouse Platform. Guide customers on best practices for data pipelines, data modeling, and platform governance. Advise on integrating Databricks with hyperscaler environments (AWS, Azure, GCP) and adjacent data tooling. Demonstrate Databricks capabilities across Data Engineering, Data Science, ML, and Generative AI use cases, including Mosaic AI, MLflow, and Feature Store. Identify and mitigate technical risks early so delivery teams are set up for success. Translate complex technical concepts into clear business value for both technical stakeholders and executive audiences. Partner with account teams throughout the sales process – from early prospect conversations through evaluation – to shape sound, winning technical strategies Collaborate with Data Scientists and ML Engineers to develop AI-powered demo assets and reference architectures. Technical Leadership & Community Serve as a resident Databricks expert within BIG — sharing knowledge and enabling the broader team. Contribute reusable accelerators, demo assets, and technical playbooks. Stay current on Databricks platform releases and evolving data and AI patterns. Represent BIG at customer events, webinars, and Databricks partner activities. Provide field feedback to Databricks product and partner teams to help influence the roadmap. Travel up to 15% for customer meetings and partner collaboration. What You Bring 3+ years of hands-on experience with Databricks and/or Snowflake in a technical capacity. 5+ years in customer-facing technical roles — solutions architecture, technical consulting, or sales engineering. Experience designing, presenting, and delivering production data architectures for enterprise customers – including Lakehouse, Delta Lake, and Unity Catalog Patterns – on AWS, Azure, and/or GCP. Databricks Professional-level certification (e.g., Data Engineer Professional, Machine Learning Professional). Strong expertise in at least one core data domain: big data engineering (Spark, Kafka), Data Warehousing & ETL, or Data Science & ML. Fluency in Python and SQL (Scala, Java, or R is a plus). Exceptional verbal and written communication and presentation skills - able to engage in and lead business-level meetings with technical and non-technical Client and internal team members. Ability to translate complex topics into clear business value and earn buy-in from engineers and executives. Nice to Have A degree in Computer Science, Applied Mathematics, Operations Research, or a related quantitative field. Experience with adjacent technologies such as dbt, Fivetran, Airflow, or Delta Sharing. Familiarity with AI/GenAI frameworks and LLM application patterns. Databricks GenAI Engineer Associate certification. Exposure to enterprise engagement cycles and how technical decisions shape deal outcomes. Experience with Frontier LLMs such as Claude code for SDLC acceleration. Why Bits In Glass? Work on meaningful, high-impact data and AI projects for enterprise clients across Canada, the US, UK, and India. Join a Certified Great Place to Work with a people-first, collaborative culture. Access to 10+ cutting-edge technology practices and continuous learning opportunities. Competitive compensation, benefits, and a team that celebrates wins together. Flexible, remote-friendly work environment. Originally posted on Himalayas

Job Title: Lakehouse Architect / Databricks SME Job Category: Information Technology Time Type: Full time Minimum Clearance Required to Start: None Employee Type: Regular Percentage of Travel Required: None Type of Travel: None * * * The Opportunity: CACI is seeking an expert Lakehouse Architect / Databricks Subject Matter Expert to support the Department of Homeland Security (DHS) Office of the Inspector General (OIG). This role offers a unique opportunity to architect and implement a modern enterprise data platform that transforms how federal oversight professionals access, analyze, and derive insights from investigative and operational data. As a Lakehouse Architect / Databricks SME, you will design and lead the implementation of a secure, scalable data lakehouse using Azure Databricks and Azure Data Lake that serves as the authoritative data foundation for AI, advanced analytics, and investigative workflows. You will architect tiered storage zones, design data catalog integration, establish compute configurations optimized for diverse analytical workloads, and modernize analyst workflows from local desktop processing to collaborative, cloud-based environments. From supporting relational, graph, and geospatial data models to enabling machine learning infrastructure, you will shape the technical architecture that powers insights from investigative records, hotline complaints, and federal datasets. Working within secure Azure Government environments, you will build the data platform foundation for a transformational program of national importance. Join us to make a meaningful impact by architecting the enterprise data infrastructure that enables next-generation federal oversight capabilities. Responsibilities: Lead the design and implementation of a secure, scalable enterprise data lakehouse platform using Azure Databricks, Azure Data Lake Storage, Delta Lake, and Unity Catalog to centralize investigative, operational, and analytical data Architect lakehouse storage zones supporting tiered data organization (raw/bronze, curated/silver, analytics-ready/gold) with data quality, transformation, and governance controls at each layer Design and implement environment configurations including workspace architecture, compute cluster strategies, autoscaling policies, job orchestration, and cost optimization approaches for diverse analytical and AI/ML workloads Design data catalog integration, metadata management, and SQL-accessible tables/views over stored files to enable governed data discovery, lineage tracking, and self-service analytics Support multiple analytical models and use cases including relational data warehousing, graph/network analysis for investigative linkages, geospatial analytics, and machine learning feature engineering Lead modernization of analyst and data scientist workflows from local workstation-based processing (Excel, R scripts, desktop tools) to collaborative, cloud-based notebooks, SQL analytics, and platform-native tools Provide technical expertise and surge support for complex data architecture challenges, analytical database design, performance optimization, and specialized data analysis requirements Design and implement machine learning engineering infrastructure including MLflow integration, feature stores, model training environments, and integration patterns between Databricks and AI platform services Develop technical content for data platform training, best practices guidance, workflow documentation, and user enablement materials tailored to investigators, analysts, auditors, and data scientists Collaborate with Government stakeholders, data engineers, AI engineers, and governance specialists to align lakehouse architecture with mission analytics requirements, data governance policies, and Agile delivery processes. Qualifications: Required – Bachelor's degree + 15 years of experience in data architecture, data engineering, analytics engineering, or related field; equivalencies considered (Master's + 12 years; 21 years with no degree; AA + 17 years) Must be able to obtain a Active DHS/ EOD Clearance as required. Deep expertise in Azure Databricks with demonstrated experience architecting and implementing lakehouse solutions using Delta Lake, Unity Catalog, and medallion architecture patterns Proven experience designing enterprise data platforms supporting diverse analytical workloads including SQL analytics, data science notebooks (Python, R, Scala), machine learning, and visualization integration Strong background in data modeling across multiple paradigms including dimensional modeling, relational databases, graph databases, and data lake/lakehouse architectures Extensive hands-on experience with Azure Data Lake Storage, PySpark, SQL, performance optimization, compute configuration, and cost management for cloud analytics platforms Desired – Experience implementing Databricks in Azure Government or other secure government cloud environments (AWS GovCloud, secure enclaves) with understanding of FedRAMP, NIST 800-53, and federal security requirements Hands-on experience integrating Databricks with Azure AI services, MLflow, feature engineering frameworks, and supporting machine learning operations (MLOps) and AI/ML model pipelines Background in federal government, law enforcement, investigative analytics, or national security data environments with understanding of sensitive data handling, data governance, and analytical workflows for oversight missions - What You Can Expect: A culture of integrity. At CACI, we place character and innovation at the center of everything we do. As a valued team member, you’ll be part of a high-performing group dedicated to our customer’s missions and driven by a higher purpose – to ensure the safety of our nation. An environment of trust. CACI values the unique contributions that every employee brings to our company and our customers - every day. You’ll have the autonomy to take the time you need through a unique flexible time off benefit and have access to robust learning resources to make your ambitions a reality. A focus on continuous growth. Together, we will advance our nation's most critical missions, build on our lengthy track record of business success, and find opportunities to break new ground — in your career and in our legacy. Pay Range : There are a host of factors that can influence final salary including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications. Our employees value the flexibility at CACI that allows them to balance quality work and their personal lives. We offer competitive compensation, benefits and learning and development opportunities. Our broad and competitive mix of benefits options is designed to support and protect employees and their families. At CACI, you will receive comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits. Since this position can be worked in more than one location, the range shown is the national average for the position. The proposed salary range for this position is: $114,600-$252,100 CACI is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, age, national origin, disability, status as a protected veteran, or any other protected characteristic.

Senior Solutions Architect (Databricks Specialist)

Blue Pearl

United States

Category: IT Services Location: We are seeking an experienced Senior Solutions Architect specializing in Databricks to provide strategic leadership and architectural oversight for a large-scale data modernization program within a leading Financial Services organization. The client is currently transitioning from a traditional SQL Server and Microsoft-centric data ecosystem to a modern Databricks-based platform to support its long-term data, analytics, and AI strategy. While the client has an established and capable Data Engineering team, they require a senior-level architect to provide strategic direction, implementation frameworks, architectural governance, and best-practice guidance to ensure a successful and cost-effective transformation. This role will focus on defining the target-state architecture, establishing standards and governance, optimizing platform design, and ensuring alignment between technology investments and business objectives. Key Responsibilities Provide strategic architectural leadership for the organisation's Databricks implementation and data modernization initiatives. Design and define enterprise-scale data and analytics architectures aligned to business and AI objectives. Develop and implement architectural frameworks, standards, patterns, and best practices for Databricks adoption. Guide the Data Engineering team on solution design, scalability, performance optimization, security, and governance. Assess current SQL Server and Microsoft-based environments and define migration strategies to Databricks. Ensure architecture decisions support future AI, machine learning, advanced analytics, and reporting requirements. Evaluate and optimize platform utilization to drive cost efficiency and maximize return on investment. Establish governance, architecture review processes, and implementation roadmaps. Provide executive-level insights and recommendations on technology direction, risks, opportunities, and investments. Collaborate with business stakeholders, technology leadership, engineering teams, and vendors to drive successful outcomes. Oversee solution quality and ensure alignment with enterprise architecture principles and regulatory requirements. Identify technical risks, dependencies, and potential challenges, implementing mitigation strategies where required. Mentor engineering teams and promote architectural excellence across the program Requirements Required Technical Skills Essential Deep expertise in Databricks architecture, implementation, and optimization Strong understanding of enterprise data platforms and modern data architectures Data Lakehouse architecture design and implementation Data governance, security, compliance, and data management frameworks Data migration strategy and execution Enterprise integration patterns and cloud-based architectures Analytics, Business Intelligence, and AI/ML platform enablement Preferred Experience with Microsoft Azure Data Services Azure Data Factory Azure Synapse Analytics SQL Server Delta Lake Unity Catalog DataOps and DevOps practices AI and Machine Learning platform architecture Essential Experience & Qualifications 10+ years of experience in Solution Architecture, Enterprise Architecture, or Data Architecture roles. Demonstrated experience delivering large-scale data transformation and modernization initiatives. Extensive experience designing and implementing Databricks solutions in enterprise environments. Proven track record supporting cloud migration and modern data platform programs. Experience within Financial Services, Banking, Insurance, or highly regulated environments. Strong understanding of data governance, security, compliance, and risk management frameworks. Experience developing enterprise architecture standards, frameworks, and governance models. Relevant certifications in Databricks, Cloud Platforms (Azure preferred), TOGAF, or related disciplines are highly advantageous. Key Competencies Strategic Leadership Ability to align technology architecture with long-term business strategy. Strong commercial acumen and focus on value delivery. Ability to influence technology direction at executive level. Stakeholder Engagement Comfortable engaging with C-suite executives and senior business leaders. Strong communication, presentation, and facilitation skills. Ability to simplify complex technical concepts for non-technical audiences. Architecture & Governance Excellent architectural design and decision-making capabilities. Strong focus on governance, standards, and best practices. Ability to drive consistency across multiple teams and initiatives. Delivery & Outcomes Results-driven with a focus on business impact and measurable outcomes. Strong problem-solving and analytical thinking skills. Ability to work independently while guiding large technical teams. Ideal Candidate Profile The ideal candidate is a highly experienced Senior Solutions Architect with deep Databricks expertise, capable of providing strategic oversight to an established engineering team. They will bring extensive experience in enterprise data transformation, architecture governance, and cloud-based analytics platforms. The successful individual will be comfortable operating at executive level, influencing business and technology strategy, while ensuring Databricks is implemented in a scalable, cost-effective, and future-ready manner that supports the organisation's AI and data ambitions. Details Originally posted on Himalayas

About the Role We are a growing MarTech consultancy and certified Salesforce implementation partner serving clients across banking, healthcare, insurance, and retail. Our team of seasoned technologists delivers end-to-end CRM, marketing automation, and data solutions — and we're looking for a Resident Solution Architect (Databricks) to join us. In this role, you'll be a trusted technical leader who bridges strategy and execution — designing scalable architectures, guiding clients through complex data platform decisions, and collaborating across cross-functional teams to drive measurable outcomes. What You'll Do Design and deliver end-to-end solution architectures with a focus on Databricks and modern data platforms Lead technical discovery and architecture discussions with clients, translating complex trade-offs into clear, actionable recommendations for non-technical stakeholders Serve as the primary technical point of contact for client engagements, ensuring solutions align with business goals and compliance requirements (e.g., HIPAA, SOX where applicable) Collaborate with delivery teams to ensure architectural integrity throughout implementation Contribute to internal best practices, reference architectures, and knowledge-sharing initiatives Support pre-sales and scoping activities by providing architectural guidance and effort estimates What We're Looking For Required: Hands-on experience designing and delivering end-to-end solution architectures Demonstrated expertise with Databricks (e.g., Unity Catalog, Delta Lake, Databricks SQL, MLflow, or Databricks Workflows) Ability to communicate architectural concepts and trade-offs clearly to non-technical stakeholders Proven track record of leading technical discussions with clients and cross-functional teams Experience working in or with consulting, professional services, or client-facing environments Nice to Have: Background in MarTech, CRM, or data cloud ecosystems (e.g., Salesforce Data Cloud, CDP platforms) Familiarity with cloud platforms (AWS, Azure, or GCP) and data lakehouse patterns Experience in regulated industries such as healthcare, financial services, or insurance Prior experience at a large systems integrator or management consultancy Compensation & Benefits Competitive compensation (details shared during the interview process) Flexible engagement model with US-based team Work with a high-caliber team and marquee enterprise clients Please note: Visa sponsorship is not available for this role. Location This role is open to candidates based in the United States. Work arrangement details will be discussed during the hiring process. Originally posted on Himalayas

Senior Cloud Data Architect – Azure / Databricks San Jose, CA (Onsite) 15+ Years must Must-Have Skills: * Data Architecture & Modeling * Azure Data Lake * Azure Data Factory (ADF) * Azure Synapse Analytics * Databricks * Apache Spark * Metadata Management & Data Governance * Data Lineage * Python * SQL * Schema Design & Evolution * Architecture Documentation / Data Flow Diagrams * Cloud Data Architecture (3+ years) * 7+ years Data Engineering / Architecture * Bachelor’s Degree in Computer Science

Principal Architect - Databricks

Tiger Analytics

United States

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world. Job Summary We are seeking a highly skilled Principal Data Architect to design and implement our next-generation data ecosystem. You will lead the technical strategy for end-to-end data management, data warehousing, and IoT ingestion pipelines. The ideal candidate brings mastery in cloud data platforms (Azure or AWS) and advanced data governance. Key Responsibilities Data Architecture: Design Databricks-driven enterprise data warehousing (EDW), lakehouse, and business intelligence (BI) systems. IoT & Stream Ingestion: Build scalable pipelines using Azure Hub, Device SDK, DPS, and Stream Analytics. Data Management: Implement information lifecycle management (ILM) from data ingestion to archiving. Data Strategy: Define, build, and enforce global data governance and master data management practices. Dataset Creation: Extract and manipulate unstructured data into connected datasets for advanced analytics. Requirements Core Cloud Data Platform (Must Have) Databricks: Strong proficiency in building optimized spark pipelines, delta lakes, and lakehouses. Cloud Ecosystem (Option A: Azure Suite) IoT Infrastructure: Azure Hub, Device SDK, Device Provisioning Services (DPS), and Device Twins. Compute & Storage: Azure Functions, Cosmos DB, and Azure Stream Analytics. Cloud Ecosystem (Option B: AWS Alternative) IoT Infrastructure: AWS IoT Core, IoT Device Management, and IoT Device Defender. Compute & Storage: AWS Lambda, DynamoDB, Amazon Kinesis, and EMR. Data Engineering & Governance BI & EDW: Deep expertise in enterprise data warehousing and business intelligence tools. Data Modeling: Proven ability to manage both structured and unstructured data assets. Qualifications & Soft Skills Communication: Ability to translate complex technical concepts clearly to diverse technical teams. Collaboration: Demonstrated teamwork skills with a proven track record in cross-functional environments. Experience: Extensive background in end-to-end data management principles and data lifecycle execution. Good to have-Experience in architecting and building Azure IoT platforms/apps with good exposure to containerization and server less architecture. Benefits Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, challenging, and entrepreneurial environment, with a high degree of individual responsibility. Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law. Originally posted on Himalayas

Principal Architect/Solution Architect Senior Director (Databricks)

Acxiom

United States

The Principal Solution Architect is a senior leadership role that blends hands-on delivery accountability with executive-level strategy. This role ensures solutions are not only well-designed, but successfully implemented and realized within client environments. This individual serves as a trusted advisor to clients, owning the end-to-end solution lifecycle—from pre-sales through implementation—while driving technical excellence, client value, and business outcomes. Client Leadership & Solution Strategy Serve as a strategic advisor to clients, aligning technical solutions with business objectives and long-term vision Lead solution design for complex, enterprise-scale engagements across multiple clients or industries Ensure all solutions align with enterprise architecture standards and technical strategy Act as the primary technical escalation point for assigned clients Pre-Sales & Solution Development Lead technical pre-sales activities including discovery, solution framing, and proposal development Own scoping, estimation, and cost modeling for large and complex opportunities Review and validate proposals for technical integrity, feasibility, risk, and alignment to standards Deliver impactful technical presentations tailored to varying stakeholder audiences Delivery & Implementation Oversight Own the transition from pre-sales to delivery, ensuring continuity and execution success Provide ongoing leadership and oversight throughout implementation Ensure solutions are scalable, optimized, and deliver measurable client value Drive successful adoption and realization of solutions within client environments Thought Leadership & Continuous Improvement Develop and share technical best practices, frameworks, and reusable assets Act as a domain expert within assigned industries or solution areas Stay current on industry trends, emerging technologies, and competitive landscape Identify and drive process improvements that enhance client outcomes and profitability Collaboration & Mentorship Partner with internal product, engineering, and delivery teams to influence product direction Mentor and guide less experienced architects and team members Foster cross-functional alignment and promote standard methodologies and best practices Core Competencies Deep expertise in enterprise solution architecture and design for complex systems Strong understanding of identity resolution (deterministic and probabilistic matching, offline/online stitching) Hands-on experience with modern cloud data platforms such as Snowflake, Databricks, or similar Knowledge of AI/ML concepts applied to large-scale data processing and analytics Experience designing real-time data architectures and Customer Data Platforms (CDP / Customer 360) Strong business acumen with the ability to communicate technical value to non-technical stakeholders Exceptional communication, relationship-building, and leadership skills Qualifications (Required) 15+ years of combined experience in technical pre-sales and solution implementation 15+ years of experience in client-facing roles, including executive-level engagement 5+ years of experience in data-driven marketing environments (database, direct, or digital marketing) Bachelors Degree and/or equivalent experience Cloud platform expertise (AWS, Azure, or GCP) Non-cloud to cloud migration strategies Snowflake, Databricks, or similar data platforms Clean room technologies Customer Data Platforms (CDP / Customer 360) Real-time data processing architectures AI/ML-enabled analytics solutions Primary Location City/State: Homebased - Conway, Arkansas Additional Locations (if applicable): Acxiom is an equal opportunity employer, including disability and protected veteran status (EOE/Vet/Disabled) and does not discriminate in recruiting, hiring, training, promotion or other employment of associates or the awarding of subcontracts because of a person's race, color, sex, age, religion, national origin, protected veteran, military status, physical or mental disability, sexual orientation, gender identity or expression, genetics or other protected status. Attention California Applicants: Please see our CCPA/CPRA Privacy Act notice here. Attention Colorado, California, Connecticut, Maryland, Nevada, New Jersey, New York City, Ohio, Rhode Island, and Washington Applicants: This position is not located in the aforementionedlocationsbut applications for remote work may be considered. For information about this role under state or local equal pay or pay transparency laws, please . Originally posted on Himalayas

1150 - Senior Data Platform Architect - Palantir Foundry & Databricks Integratio

GoFasti

Remote

We Make Remote Work Remarkable • TopTalent from LatAm Hello! We are GoFasti, a Talent-as-a-Service. GoFasti bridges the gap between world-class developers and designers from LatAm and first-class companies around the globe. We need an English-fluent Senior Data Platform Architect - Palantir Foundry & Databricks Integration, based in Latin America, available to work remotely. We are looking for someone with exceptional communication and relationship-building skills, who embraces changes while maintaining strong attention to detail. An interested and proactive person, who's constantly learning and improving their skills. Are you the one we are looking for? Responsibilities: Design and implement enterprise-scale federated architectures integrating Palantir Foundry and Databricks. Establish standards for data sharing across Foundry, Databricks, BigQuery, and Cloud Storage environments. Define architecture patterns leveraging Delta Lake, Apache Iceberg, Unity Catalog, Foundry Ontology, Virtual Tables, and Catalog Federation. Lead the modernization of legacy ETL architectures toward metadata-driven, cloud-native data products. Define enterprise data governance, lineage, metadata, and ownership models across both platforms. Create architectural roadmaps supporting AI, machine learning, real-time analytics, and self-service data consumption. Design and implement Foundry Databricks Connector solutions, including bulk imports, incremental data synchronization, virtual tables, compute pushdown, and external model integrations. Build scalable ingestion, transformation, and enrichment pipelines using PySpark, Spark SQL, Python, Databricks Workflows, Airflow, and Foundry Code Repositories. Architect secure connectivity between Palantir Foundry, Databricks, Google Cloud Platform, BigQuery, Cloud Storage, and Enterprise APIs. Enable AI and machine learning workloads across Foundry and Databricks environments. Serve as the technical authority for enterprise data platform architecture and lead architecture reviews. Requirements: 10+ years of experience in Data Engineering, Data Architecture, or Platform Engineering. 5+ years of experience with Databricks Lakehouse Architecture. Experience implementing or operating Palantir Foundry data platforms. Deep expertise in Databricks, PySpark, Spark SQL, Delta Lake, Python, and Data Modeling. Strong knowledge of Unity Catalog, Apache Iceberg, Lakehouse Architectures, Data Governance, and Metadata Management. Hands-on experience with Google Cloud Platform, including BigQuery, Cloud Storage, Pub/Sub, IAM, and Networking. Experience designing highly scalable distributed data systems. Strong architecture, leadership, and stakeholder management skills. It's a plus: Palantir Foundry certification or implementation experience. Experience with Ontology development and operational decision platforms. Experience with AI/ML infrastructure and model deployment. Familiarity with Terraform, Kubernetes, GitHub Actions, and CI/CD Pipelines. Experience with survey, consumer intelligence, marketing, or ad-tech data platforms. Experience supporting data products at Fortune 500 scale. Compensation: The salary range offered for this position varies from (USD) $6,000 - $7,000 per month, depending on seniority and skillset. This position is for a full time contract, through a payroll platform. The talent will work remotely allocated at our client. Here are the steps for this process: TBD > Application review/approval > Screening interview with GoFasti's team > We build and send your profile to our client > Profile review/approval by client > Interview with the client > Hiring and onboarding. Once you apply for the job, our team will review your resume. If it meets the requirements, we will contact you and move forward in the process. Note for Candidates Approached Directly: If you were contacted directly by a member of our team and are interested in this opportunity, please do not apply through this link. Instead, reach out to the person who contacted you to coordinate a meeting. Thank you! Originally posted on Himalayas

Senior Cloud Data Architect - Databricks Lakehouse

Peraton

United States

Responsibilities Peraton's Department of the Interior (DOI), U.S. Fish and Wildlife Service (FWS), and NOAA's National Marine Fisheries Service (NMFS) have identified a critical gap in the federal government's ability to conduct comprehensive Endangered Species Act (ESA) research. While FWS operates an authoritative web-based platform for managing data for terrestrial and freshwater species, it does not currently include NMFS marine and anadromous species data forcing agencies to rely on separate, manual processes. This program closes that gap by integrating marine and anadromous species data into the existing FWS platform, creating a single, unified experience for all ESA-listed species. Peraton is seeking a Senior Cloud Data Architect SME with expertise in Databricks and cloud data lakehouse architectures to lead the data engineering foundation for a federal data migration program. You will design and oversee the implementation of ETL pipelines, schema harmonization, and data quality frameworks within a FedRAMP-compliant hybrid AWS cloud environment. Work Location: Remote Roles and Responsibilities Lead the design and implementation of the cloud data lakehouse architecture for federal species data ingestion, ensuring compatibility with existing infrastructure and platform constraints Design the Delta Live Tables ETL pipeline architecture, defining pipeline topology, data flow patterns, transformation stages, and error-handling frameworks Lead schema harmonization activities, conducting gap analysis between source schemas and the target data model and producing field-level mapping documentation Define metadata standards for all ingested datasets including naming conventions, data types, null handling, and authoritative source attribution Design the Metadata and Authoritative Source Registry structure and population methodology Oversee ETL pipeline development and deployment, ensuring all pipelines are version-controlled and peer-reviewed Design data quality validation frameworks within ETL pipelines, defining completeness, accuracy, consistency, and spatial integrity quality criteria Produce the Data Model Harmonization Report, documenting gap analysis findings between source schemas and the target data model, field-level mapping decisions, and metadata standard definitions for government review and approval Lead the operational handoff of ETL pipeline architecture, producing documentation for routine data refresh, pipeline monitoring, and maintenance procedures Provide cloud data architecture guidance for FedRAMP-compliant production deployment Qualifications Basic Qualifications Bachelors degree and 12 years professional experience or a Masters degree and 10 years professional experience or an Associates degree and 14 years professional experience; or a high school diploma/equivalent and 16 years’ professional experience. U.S. Citizenship required; must have the ability to obtain and maintain a Public Trust clearance Extensive years of experience in cloud data architecture with expertise in Databricks and Delta Lake/Delta Live Tables Demonstrated experience designing data lakehouse architectures for large-scale data migration programs Experience with schema harmonization, ETL pipeline design, and data quality frameworks Strong knowledge of FedRAMP, FISMA, and federal cloud compliance requirements Experience with metadata management and authoritative source registry design Preferred Qualifications Databricks Certified Data Engineer or equivalent certification AWS Certified Solutions Architect or AWS Certified Data Engineer certification Experience with federal environmental or geospatial data systems Familiarity with spatial data integration and GIS data pipelines Active Public Trust Clearance Peraton Overview Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world’s leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees do the can’t be done by solving the most daunting challenges facing our customers. Visit peraton.com to learn how we’re keeping people around the world safe and secure. Target Salary Range $135,000 - $216,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual’s experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay. EEO EEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law. Originally posted on Himalayas

Azure Databricks Senior Architect

Tiger Analytics

United States

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world. This role will be responsible for Architecture, Designing and implementing best data practices on the Azure platform. Requirements Strong proficiency in Databricks. (Must have) Should have extensively worked on Azure Hub, Azure Device SDK, Azure Device provisioning services, Azure Device twins, Azure Functions, Data bricks, Cosmos DB, Azure Stream analytics. Knowledgeable in tools used to identify and manage structured and unstructured data. Must have BI, EDW, along with Data Strategy, Architecture and Governance Defined and implemented information lifecycle management practices. Strong background and working knowledge in end-to-end data management principles. Strong background in developing and utilizing tools that prepare, extract and manipulate data to create connected datasets (data warehousing) that can be utilized for analytics purposes. Strong communicator at the technical levels Demonstrated teamwork skills. Good to have- Experience in architecting and building Azure IoT platforms/apps with good exposure to containerization and server less architecture. Benefits Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, challenging, and entrepreneurial environment, with a high degree of individual responsibility. Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law. Originally posted on Himalayas