Data Engineer Jobs

Data Engineer/Senior Data Engineer

PlusAI

Santa Clara, CA

Job Description Job Description PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World’s Most Innovative Companies. Partners including TRATON GROUP’s Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams. Knowing how well our virtual driver drives — and why it fell short — is what lets us ship with confidence. In this role, you will own that loop end to end: the metrics that quantify driving performance, the pipelines that compute them at fleet scale, the analysis that turns them into judgments about autonomy behavior — including where on the map that behavior changes — the data and tooling that gate software releases, and the agentic workflows that take a detected issue from triage to a proposed fix. You will work primarily in Python across large-scale data processing, geospatial analytics, evaluation frameworks, and LLM-powered automation. We welcome engineers from data engineering, analytics, geospatial, evaluation, or robotics backgrounds; prior autonomous-vehicle experience is helpful but not required. We are open to candidates at either the Engineer or Software Engineer level. Level will be determined by experience, technical depth, scope of ownership, and demonstrated impact. You do not need experience with every technology in our stack; we value strong fundamentals, ownership, and the ability to learn. Responsibilities: Define and compute driving performance metrics — covering safety, comfort, progress, interventions, and compliance — and build the scalable pipelines that evaluate them consistently across fleet and simulation data Analyze road-test and simulation data in depth to identify trends, regressions, and anomalies in autonomy behavior, and turn them into clear findings that engineering teams act on Build geospatial analytics over fleet driving data: map-matched metrics, route and corridor performance, location-based clustering of events and issues, and geographic coverage analysis that shows where the virtual driver performs well and where it struggles Build the data foundations and tooling for release management, including release-over-release comparisons, readiness and gating criteria, and traceable evidence supporting release decisions Build AI agentic workflows that triage detected issues at scale — clustering and deduplicating failures, attributing root cause, routing to the right owners, and proposing fixes with supporting evidence for engineering review Ensure that your work is performed in accordance with the company's Quality Management System (QMS) requirements and contribute to continuous improvement efforts Required Skills: BS, MS, or PhD in Computer Science, engineering, or a related technical field, or equivalent practical experience Proficiency in Python, with experience building scalable data processing systems or evaluation frameworks Experience developing metrics and analyzing large-scale time-series, event, or geospatial data, including principled metric definitions, validation, and error analysis Experience building LLM-powered or agentic workflows for data analysis, evaluation, or automation Ability to solve open-ended technical challenges and communicate findings clearly to engineering and program stakeholders Self-driven with a strong sense of ownership: a quick learner who is eager to take responsibility and drive projects forward end to end Preferred Skills: Experience with distributed data processing such as Apache Spark, and workflow orchestration such as Airflow or Argo Workflows Familiarity with LLM agent frameworks (e.g., LangChain, LangGraph, or similar) and prompt/tool-orchestration patterns Experience with geospatial data and tooling, such as GIS formats, map matching, spatial indexing and joins, PostGIS, GeoPandas, or map-based visualization libraries Experience with release engineering, quality gating, or automated regression detection Experience with autonomous vehicles, robotics, or other safety-critical systems Experience building dashboards or analytics interfaces that expose metrics to users Your opportunities joining PlusAI Work, learn and grow in a highly future-oriented, innovative and dynamic field. Wide range of opportunities for personal and professional development. Catered free lunch, unlimited snacks and beverages. Highly competitive salary and benefits package, including 401(k) plan. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Making data-driven decisions is key to Plaid's culture. To support that, we need to scale our data systems while maintaining correct and complete data. We provide golden datasets and tooling to teams across engineering, product, and business and help them explore our data quickly and safely to get the data insights they need, which ultimately helps Plaid serve our customers more effectively. In addition, Plaid will not be successful if we can't move quickly. We build the data systems and tools that enable everyone at Plaid to be data-driven, making analytics easy, obvious, and proactive across the company. Data Engineers heavily leverage SQL and Python to build data workflows that integrate with our Golang applications. We use tools like DBT, Airflow, Redshift, Atlan, and Retool to orchestrate data pipelines and define workflows. We work with engineers, product managers, business intelligence, data analysts, and many other teams to build Plaid's data strategy and a data-first mindset. You will be in a high impact role that will directly enable business leaders to make faster and more informed business judgements based on the datasets you build. You will have the opportunity to carve out the ownership and scope of internal datasets and visualizations across Plaid which is a currently unowned area that we intend to take over and build SLAs on. You will have the opportunity to learn best practices and up-level your technical skills from our strong DE team and from the broader Data Platform team. You will collaborate with and have strong and cross functional partnerships with literally all teams at Plaid from Engineering to Product to Marketing/Finance etc. Responsibilities - Understanding different aspects of the Plaid product and strategy to inform golden dataset choices, design and data usage principles. - Have data quality and performance top of mind while designing datasetsLeading key data engineering projects that drive collaboration across the company. - Advocating for adopting industry tools and practices at the right time. - Owning core SQL and python data pipelines that power our data lake and data warehouse. - Well-documented data with defined dataset quality, uptime, and usefulness. Qualifications - 4+ years of dedicated data engineering experience, solving complex data pipelines issues at scale. - You’ve have experience building data models and data pipelines on top of large datasets (in the order of 500TB to petabytes) - You value SQL as a flexible and extensible tool, and are comfortable with modern SQL data orchestration tools like DBT, Mode, and Airflow. - You have experience working with different performant warehouses and data lakes; Redshift, Snowflake, Databricks. - You have experience building and maintaining batch and realtime pipelines using technologies like Spark, Kafka. - You appreciate the importance of schema design, and can evolve an analytics schema on top of unstructured data. - You are excited to try out new technologies. You like to produce proof-of-concepts that balance technical advancement and user experience and adoption. - You like to get deep in the weeds to manage, deploy, and improve low level data infrastructure. - You are empathetic working with stakeholders. You listen to them, ask the right questions, and collaboratively come up with the best solutions for their needs while balancing infra and business needs. - You are a champion for data privacy and integrity, and always act in the best interest of consumers. Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid! Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com. Please review our Candidate Privacy Notice here https://plaid.com/legal/#candidate-privacy-notice. Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.

Data Engineer

MFour Data Research

Kansas City, MO

MFour Data Research Jobs Data Engineer MFour Data Research Data Engineer Job Posted 5 Days Ago Posted 5 Days Ago Kansas City, MO, USA In-Office 125K-125K Annually Mid level Marketing Tech • Software Building the Future of Consumer Intelligence One Behavioral Signal at a Time The Role Design, build, and manage scalable batch and real-time data pipelines, databases, and processing systems. Develop and administer Databricks and Snowflake environments, optimize data architecture and distributed processing, manage PostgreSQL and MySQL databases, and implement governance, monitoring, alerting, and troubleshooting practices. Collaborate with analytics, engineering, and product teams to deliver reliable data solutions, document workflows, and promote modern data engineering practices. Summary Generated by Built In Welcome to MFour! Our Story: Founded in 2011, MFour is a fast-growing data and analytics technology company “democratizing” consumer insights. Named a 2023 “top 25 L.A. tech companies to watch,” by Built In, we’ve created a SaaS ecosystem, giving businesses access to united shopper behavior + opinion data that uncovers the whos, whats, whys, whens, and wheres behind consumers in ways never before possible. We help 25% of the Fortune 100 plus organizations of all sizes make product, brand, and advertising decisions. Our Product: Using the nation’s most downloaded, highest-rated, and only Apple-approved app & web data collection and survey app (Surveys On The Go®), MFour is the only consumer market research company that guarantees accurate, validated responses for every survey, giving businesses the data and insights they need to make impactful decisions. From validated opinion and behavior trackers to advertising exposure measurement, MFour is trusted by hundreds of leading companies. Our Goal: To eliminate the unknown (data blind spots) within market research in a way that recognizes a consumer’s right to privacy, so marketers can make better decisions about new and existing products, advertising choices, and competitive positioning. MFour is trusted by hundreds of leading brands, including Google, Microsoft, Samsung, Walmart, Disney, Spotify, and Lowe’s. , Our Core Values: Simplicity, Humility, Quality, Consistency, and Innovation. Your Journey to Success: The Data Engineer will design, implement, and manage scalable data pipelines, databases, and processing systems to support engineering, product, and analytics teams. This includes developing and administering platforms like Databricks and Snowflake, optimizing data architecture, and ensuring performance, scalability, and reliability. Your Mission: Data Infrastructure Development: Design, build, and maintain scalable data pipelines to process large volumes of structured and unstructured data. Optimize data architecture for both real-time and batch processing workflows. Integrate and maintain PostgreSQL, MySQL, Databricks, and Snowflake within our data ecosystem. Databricks Development and Administration: Develop and manage workflows on Databricks to support ETL/ELT processes. Optimize Databricks performance for distributed computing and data processing. Monitor, troubleshoot, and ensure the reliability of Databricks clusters and jobs. Snowflake Development and Administration: Design and optimize Snowflake schemas and data warehouses for efficient querying. Develop and manage data ingestion pipelines for Snowflake using modern tools and frameworks. Administer Snowflake environments, including account management, performance tuning, and resource optimization. Database Management: Administer PostgreSQL and MySQL databases, ensuring high availability and performance. Implement and enforce data governance practices to ensure data security and compliance. Collaboration: Partner with analytics and engineering teams to define data needs and deliver solutions for business insights. Work with product teams to align data solutions with product goals and user requirements. Monitoring and Troubleshooting: Set up monitoring and alerting systems for data platforms and pipelines. Proactively debug and resolve data-related issues to ensure system reliability. Innovation and Best Practices: Stay current with emerging trends and advocate for tools and practices that enhance data engineering efficiency. Document workflows, pipelines, and platform configurations to foster team collaboration and knowledge sharing. What Sets You Apart Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience). 3+ years of professional experience in data engineering or related fields. Proficiency in Databricks development and cluster administration. Hands-on experience with Snowflake development and administration, including performance tuning and security configuration. Strong understanding of relational databases, particularly PostgreSQL and MySQL. Expertise in programming languages like Python, Scala, or SQL for data processing and automation. Familiarity with ETL/ELT tools and frameworks such as Apache Airflow or dbt. Experience with cloud platforms (AWS, Azure, or GCP). Preferred Skills: Knowledge of distributed systems and big data frameworks like Spark. Experience with CI/CD pipelines for deploying data workflows. Familiarity with real-time streaming technologies (Kafka, Kinesis, etc.). Why Join Us? Work with a passionate, innovative team driving the next wave of industry solutions. Opportunities for professional growth and continuous learning. Competitive compensation, comprehensive benefits, and a flexible work environment. In return for your dedication, we offer: Salary $125,000 Health benefits Top-tier health benefits include; medical, dental, vision, LTD, and life insurance Mental health benefits Additional benefits Unlimited PTO In the WeWork office In the heart of the financial district in downtown Kansas City Open space concept & team-focused atmosphere Company-wide celebrations Team bonding events and happy hours CHECK US OUT: https://www.youtube.com/watch?v=cabweOxGias&t=1s OUR APP : https://surveysonthego.com/ Read Full Description Skills Required Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience 3+ years of professional experience in data engineering or related fields Proficiency in Databricks development and cluster administration Hands-on experience with Snowflake development and administration, including performance tuning and security configuration Strong understanding of relational databases, particularly PostgreSQL and MySQL Expertise in Python, Scala, or SQL for data processing and automation Familiarity with ETL/ELT tools and frameworks such as Apache Airflow or dbt Experience with cloud platforms such as AWS, Azure, or GCP Knowledge of distributed systems and big data frameworks such as Spark Experience with CI/CD pipelines for deploying data workflows Familiarity with real-time streaming technologies such as Kafka or Kinesis MFour Data Research Compensation & Benefits Highlights Healthcare Strength — The company highlights medical, dental, vision, and life insurance, plus long-term disability and free, confidential, unlimited mental-health support. The breadth of core health offerings is emphasized across career materials and job posts. Leave & Time Off Breadth — “Unlimited PTO” is promoted alongside paid holidays and sick time. Public materials position generous time off as a cornerstone of the package. Retirement Support — A company-matched 401(k) is called out in career pages and job listings. While match specifics should be confirmed, the presence of employer matching strengthens long-term value. Learn more about MFour Data Research's Compensation & Benefits → MFour Data Research Insights What's It Like to Work at MFour Data Research? MFour Data Research Culture & Values MFour Data Research Career Growth & Development What's the Work-Life Balance Like at MFour Data Research? MFour Data Research Leadership & Management MFour Data Research Company Growth, Stability & Outlook View all jobs at MFour Data Research View MFour Data Research Profile Report Job Am I A Good Fit? beta Get Personalized Job Insights. Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align. Upload Resume Upload Resume Success! Refresh the page to see how your skills align with this role. The Company HQ: Irvine, CA 98 Employees Year Founded: 2011 What We Do MFour turns consumer behavior into a competitive advantage. We operate the largest opt-in, first-party consumer panel in the U.S., tracking 4B+ monthly signals across location, apps, web, receipts, and AI conversations. Our platform, powered by DANI™, delivers instant insights to the world's biggest brands, from Google to Walmart to Disney. We're building the future of market research, and we're just getting started! Why Work With Us MFour is redefining how the world understands consumers by tracking the full journey from ChatGPT search to in-store purchase. We move fast, trust our people, and are building something that's never been built before. If you want to grow, build, and actually matter, MFour is it! MFour Data Research Offices Learn More Hybrid Workspace Employees engage in a combination of remote and on-site work. Typical time on-site: 3 days a week HQ Irvine, CA Kansas City - WeWork office Learn more Option 1 of 1 Similar Jobs MFour Data Research Account Executive Marketing Tech • Software In-Office 2 Locations 98 Employees 120K-120K Annually View all jobs at MFour Data Research View MFour Data Research Profile Report Job Continue Not Eligible Save You are not eligible to apply because your location does not meet the criteria for this role. Not Eligible Save Apply Instructions Sign up now Access later Create Free Account Already have an account? 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Data Engineer

Dropbox

United States

Role Description As a Data Engineer on Analytics Data Engineering, you will build and operate the pipelines and data models the rest of Dropbox relies on to understand its products and its business. You will own well-scoped pipelines end to end — design, build, test, ship, monitor — with senior engineers alongside you for the harder architectural calls. Your work feeds the datamarts and KPIs used by data science, product, and company leadership, so the quality of what you build is visible quickly. This is a build-oriented team on a modern stack rather than a maintenance role, and a strong place to develop into an engineer who can own a full data domain. Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here. Responsibilities Build and maintain Spark and SparkSQL jobs that populate company data models Own well-scoped pipelines end to end, from requirements through deployment, monitoring, and iteration Contribute to data quality frameworks, testing, and data lineage instrumentation Partner with data scientists, analysts, product managers, and engineers to turn data needs into durable models Extend datamarts and data models supporting recurring reporting and analysis across products Improve the reliability and cost efficiency of existing pipelines, dashboards, and frameworks Participate in a business-hours on-call rotation and help improve runbooks and alerting Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying. Requirements 2+ years of development experience in Spark, Python, Java, C++, or Scala 2+ years of SQL experience, including query performance tuning 2+ years of experience with schema design and dimensional data modeling Experience building and maintaining production data pipelines that others depend on Working exposure to a cloud data lake or lakehouse platform, Databricks preferred Clear written and verbal communication with non-engineering partners, and a track record of asking for help and feedback early BS in Computer Science or a related technical field involving coding(e.g. physics or mathematics), or equivalent technical experience Preferred Qualifications 4+ years of SQL experience Experience with medallion architectures and incremental data modeling patterns Experience with Airflow or a similar orchestration framework Exposure to data quality monitoring using Monte Carlo or similar tools Exposure to streaming architectures(Kafka, Kinesis, Structured Streaming) Durable Skills AI fluency means using these tools to amplify human judgment, not replace it. We believe people with these skills will thrive as work and technologycontinue to evolve: Awareness:Understand yourself and others. Judgment:Evaluate information and make decisions in complex situations. Adaptability:Learn, adjust, and stay effective through change. Connection:Communicate, collaborate, and build trust. To learn more about why these skills matter and what the data shows about thriving through change, read this blog postfrom our Chief People Officer, Melanie Rosenwasser. Compensation US Zone 1 This role is not available in Zone 1 US Zone 2 $120,900—$163,500 USD US Zone 3 $107,400—$145,400 USD Originally posted on Himalayas

Job Title: Remote Data Engineer Location: Remote (U.S. Only) Job Type: Full-time Job Summary: We are seeking a talented Data Engineer to build and optimize scalable data pipelines and infrastructure. This role is 100% remote, but applicants must be based in the U.S. You will work closely with data scientists, analysts, and software engineers to ensure seamless data integration and support business intelligence efforts. Key Responsibilities: Develop, optimize, and maintain data pipelines and ETL processes. Design and manage scalable data storage solutions, including data lakes and warehouses. Implement data governance, security, and compliance best practices. Monitor, troubleshoot, and improve data pipeline performance. Collaborate with cross-functional teams to support data-driven decision-making. Work with cloud platforms (AWS, GCP, Azure) to manage large-scale data processing. Automate data ingestion, transformation, and validation tasks. Required Qualifications: Bachelor's or Masters degree in Computer Science, Data Engineering, or a related field. Strong proficiency in SQL, Python, or Scala. Hands-on experience with Apache Spark, Hadoop, or Airflow. Solid understanding of relational (SQL) and NoSQL databases. Experience with cloud data platforms (AWS Redshift, Google BigQuery, Azure Synapse). Familiarity with CI/CD and DevOps practices for data engineering. Strong analytical and problem-solving skills. Preferred Qualifications: Experience with real-time data streaming technologies (Kafka, Flink). Knowledge of machine learning pipelines. Understanding of data privacy regulations (GDPR, CCPA). Benefits: Competitive salary and performance-based bonuses. Flexible work hours with a fully remote setup. Health, dental, and vision insurance. 401(k) with company matching. Generous paid time off and parental leave. Originally posted on Himalayas

Data Engineer

ZipLiens

Franklin, United States

Zipliens is a leading lien resolution company that specializes in streamlining the lien process for personal injury law firms. We are looking for proactive, results-driven individuals to join our dynamic team. We're seeking a Data Engineer to help shape the foundation of Zipliens' growing data ecosystem. Our engineering team supports a diverse set of tools and systems that power lien resolution operations, client transparency, and decision-making across the company. In this role, you'll design and maintain reliable data pipelines, optimize data storage and retrieval, and contribute to the design of Zipliens information architecture to balance data security, data integrity, and report performance. You’ll examine and model data to ensure that our systems and reporting deliver accurate, timely, and actionable insights. This role requires close collaboration and clear communication with data analysts, product owners, and engineers to build scalable data infrastructure, with the initiative to identify and address problems proactively, and contribute to data quality standards that will support the next generation of Zipliens applications.

Data Engineer

Parvana

United States

Category: IT Services Location: About our client: Our client develops and supports software and data solutions across a variety of industries. They want you to get ahead of the market and stay there. They offer a combination of plug and play products that can be integrated with existing systems and processes and can also be customised to client needs. Their capabilities extend to big data engineering and bespoke software development, solutions are available as both cloud-based and hosted. What you will be doing: Analyzes complex customer data to determine integration needs. Develops and tests scalable data integration/transformation pipelines using PySpark, SparkSQL, and Python. Contributes to the codebase through coding, reviews, validation, and complex transformation logic. Automates and maintains data validation and quality checks. Collaborates with FPA, data engineers, and developers to align solutions with financial reporting and business objectives. Participates in solution architecture and technical discussions, refining user stories and acceptance criteria. Utilizes modern data formats/platforms (Parquet, Delta Lake, S3/Blob Storage, Databricks). Partners with the product team to ensure accurate customer data reflection and provide feedback based on data insights. What our client is looking for: A Data Analytics Engineer with 5+ years of experience. Must have strong Python, PySpark, Notebook, and SQL coding skills, especially with Databricks and Delta Lake. Proven ability to build and deploy scalable ETL pipelines to cloud production environments using CI/CD. Experience with Agile/Scrum, data quality concepts, and excellent communication is essential. Cloud environment (Azure, AWS) and Infrastructure as Code (Terraform, Pulumi) experience beneficial. Telecoms industry or consulting experience, plus accounting knowledge, is a plus. Job ID: J106998 For a more comprehensive list of opportunities that we have on offer, do visit our website - Requirements Data Engineer, PySpark, Python, SQL, Databricks, ETL, CI/CD, Cloud, Azure, AWS Details Originally posted on Himalayas

Data Engineer

KIS Solutions

United States

This is a remote position. We are looking for Data Engineers (Junior, Mid or Senior)! At KIS, we are always looking for talented individuals to join our team for future opportunities. If you are a Data Engineer and interested in working on innovative projects with one of our global clients, sign up for our Talent Pool! MainResponsibilities: Design, build, and maintain end-to-end data pipelines (batch and/or streaming), from ingestion to transformation and delivery. Develop and operate ETL/ELT workflows, ensuring reliability, scalability, and performance. Write efficient, production-grade SQL queries for data extraction, transformation, and analytics use cases. Implement and maintain data models (e.g., star schemas, incremental models) optimized for analytics and reporting. Develop reusable and modular Python code for data transformations and pipeline logic. Monitor data pipelines, troubleshoot failures, and perform root cause analysis across code, orchestration, data sources, and cloud services. Ensure data quality by implementing automated validation checks (schema validation, freshness checks, row-level assertions). Translate business and analytical requirements into robust technical data solutions. Collaborate with analysts, backend engineers, and other stakeholders to define data contracts and ensure data availability. Actively participate in planning, estimation, and prioritization of data engineering tasks. Proactively identify risks related to performance, scalability, or data integrity and propose mitigation strategies. Contribute to continuous improvement of data platforms, processes, and team practices. Write and maintain technical documentation for pipelines, schemas, and data lineage. Communicate clearly with team members and clients, raising questions and concerns when requirements or priorities are unclear. Support and mentor other team members when appropriate, contributing to overall team delivery. Requirements Professional experience as a Data Engineer working with production data pipelines. Strong experience with SQL, including query optimization, indexing, partitioning, and performance trade-offs. Professional experience writing Python for data transformations, following good design and modularization practices. Experience designing and implementing data models for analytics use cases. Experience building and operating pipelines using cloud-based data platforms. Hands-on experience with Azure, Databricks, and Data Lake environments. Experience operating data pipelines, including error handling, monitoring, and data quality processes. Familiarity with Git for version control, including branching and resolving merge conflicts. Experience working with Kubernetes or containerized data workloads. Understanding of data formats such as Parquet or ORC, including cost and performance considerations. Knowledge of basic data security and governance practices (access control, masking, PII handling). Ability to deliver less complex tasks independently and more complex tasks with guidance. Strong sense of ownership, responsibility, and accountability for data workflows. Good organizational and time management skills, with the ability to estimate and meet delivery deadlines. Advanced English for collaboration with global clients. Team-oriented mindset with strong communication and problem-solving skills. Live in Latin America region.​ Nice to Have Experience with data orchestration tools (e.g., Airflow, Azure Data Factory, or similar). Exposure to CI/CD for data pipelines and deployment automation. Experience with streaming data (e.g., Kafka, Event Hubs). Familiarity with data observability and monitoring tools. Experience collaborating with Machine Learning or advanced analytics teams. Experience working with Java Spring Boot in data engineering projects. Originally posted on Himalayas

Data Engineer

NinjaHoldings

United States

NinjaHoldings was founded in 2017 by a team seeking to revolutionize the way everyday Americans interact with financial services. Through our CreditNinja and NinjaCard brands, we empower people overlooked by traditional financial institutions to take control of their finances via a full suite of digital banking and lending products, providing incentives and rewards along the way as we guide them on a path to financial improvement. Through our NinjaEdge brand, we help companies better understand their customers by offering a package of bespoke underwriting, fraud detection, and analytics services. With offices in Chicago, Miami, and around the world through the power of remote work, we are a lean and innovative team always seeking like-minded talent to join us in our fight to disrupt consumer finance. Job Summary We are looking for a Data Engineer to join a team of analytics and machine learning experts. The hire will be responsible for building tooling to support analytics, helping to extend our machine learning platform, expanding and optimizing our data pipeline architecture, supervising junior engineers, and interfacing with the Development team to create cross-team solutions. The ideal candidate is an experienced data engineer and data wrangler who enjoys optimizing data systems and building them from the ground up. They must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products. Experience in analytics and statistics is a major bonus. The right candidate will be excited by the prospect of optimizing or even re-designing, our company’s data architecture to support our next generation of products and data initiatives; as well as mentoring and guiding junior members of the team. Key Responsibilities: Supervise junior members of the data engineering team. Guiding, planning, and reviewing the team's work Create and maintain optimal data pipeline architecture Assemble large, complex data sets that meet functional / non-functional business requirements Extend our machine learning platform by designing tools that interface with cloud services, our current code base, and provide new flexibility in model building Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Python, and AWS Build analytics tools to provide actionable insights into key business performance metrics, as well as supporting the needs of the analytics team Create data-handling tools for analytics and data scientist team members that assist them in building and optimizing our decision-making process Ideal Candidate Will Have: 3+ years of experience in a Data Engineer role Bachelors degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field Advanced working SQL knowledge and experience working with relational databases (including Postgres and MySQL), query authoring (SQL), as well as working familiarity with a variety of databases Experience building data pipelines, architectures, and data sets from raw, loosely structured data A history of focusing on test driven design and results for repeatable and maintainable processes and tools Experience building processes supporting data transformation, data structures, metadata, dependency, and workload management Working knowledge of message queuing, stream processing, and highly scalable data stores Strong project management and organizational skills and the ability to work independently in a fast-paced, quickly changing environment. Ability to keep up with several projects at once and understand the impact of projects within a larger system Experience supporting and working with cross-functional teams in a dynamic environment Experience managing junior engineers and guiding a team of engineers through project planning, execution, and quality control stages Candidate should have experience using the following software/tools: Experience with object-oriented design in Python Experience with data pipeline and workflow management tools Experience with AWS cloud services: EC2, RDS, Redshift, Glue, S3 Additional Pluses: Strong analytic skills and understanding statistical methodologies Experience building machine learning models Experience handling data from acquisition to usage in models Experience building and maintaining RestAPI systems, Flask apps, and state machines Experience with continuous integration, especially in a data science context Experience with Ruby on Rails Benefits: Competitive salary and benefits package Flexible, remote work Fun, fast-paced work environment Dynamic start-up culture Ability to make an immediate impact in a growth stage company Convenient downtown Chicago office located in the heart of the city Equal opportunity employer IMPORTANT NOTICE: Please carefully review communications to ensure that they are from the official Breezy applicant tracking platform (@ninjaholdings.breezy-mail.com) or an official NinjaHoldings brand email: @ninjaholdings.com, @creditninja.com, @ninjacard.com, or @edgescore.com. If you have been contacted regarding a job opening at NinjaHoldings from any other email address, including similar email variations, this is NOT a trusted source. We recommend that you refrain from responding to suspicious emails and file a complaint with the FBI's Internet Crime Complaint Center (IC3) at For questions or to confirm the authenticity of a communication, please email hr @ninjaholdings.com. Salary: $100,000 – $145,000 / year Originally posted on Himalayas

Job Details: Level: Senior, Job Location: 7265 WINDSOR BLVD SUITE 106 - Windsor Mill, MD, Education Level: 4 Year Degree, Salary Range: $121600.00 - $163800.00Salary/year, Company Overview Index Analytics, LLC, is a rapidly growing, Baltimore-based small business providing health-related consulting services to the federal government. At the center of our company culture is a commitment to instilling a dynamic and employee-friendly place to work. We place a priority on promoting a supportive and collegial team environment and enhancing staff experience through career development and educational opportunities. Position Overview Index Analytics is seeking a Data Engineer to support Government clients to design, build, and optimize scalable data pipelines and cloud-based solutions. The Data Engineer plays a key role in modernizing the organization’s data ecosystem by implementing data solutions using a contemporary infrastructure. As part of a cross-functional team including Data Engineers, Software Engineers, Analysts, the engineer will support efforts to implement a robust environment capable of ingesting diverse data sources to support advanced analytics and reporting needs. Core responsibilities include implementing structural, interface, and business requirements for data solutions; implementing relational and non-relational databases and their associated integration components; and implementing a Snowflake-based system with automated data pipelines. This role blends advanced data engineering with hands‑on cloud solutions engineering, leveraging AWS, Snowflake, and modern DevOps practices. The ideal candidate has experience delivering high‑quality solutions in an Agile environment. Responsibilities Collaborate closely with stakeholders, cross‑functional and internal technical teams to understand requirements and business rules and develop a thorough understanding of the business context and objectives Collaborate to implement secure, scalable, and cost‑optimized data solutions Build and maintain scalable, reliable ETL/ELT data pipelines using AWS, Snowflake and Snowflake tools Develop and optimize data models, both conceptual and physical, to support analytics, reporting, dashboards and operational consumption Implement data quality, validation, and monitoring frameworks to ensure accuracy and reliability Ensure data workflows are modular, testable, and properly version‑controlled Operationalize pipelines with monitoring, alerting, and automated recovery mechanisms Conduct advanced data analysis using languages such as Python and SQL Support the development of documentation to include data models, data dictionaries, and data usage guides Improve end-to-end performance of data workflows Build and maintain CI/CD pipelines to support automated testing, deployments, and continuous integration Meet schedule deadlines and commitments with a high-level of quality of deliverables Collaborate with a team of cross-functional resources in an Agile delivery environment to deliver iterative value Qualifications: US citizen or lived in the US for 3 of the last 5 years. Must be able to obtain a U.S. Federal government client badge and pass a government background investigation Bachelor’s degree or equivalent with six (6) or more years of experience as a Data Engineer or similar role Strong proficiency in Snowflake, AWS services Hands-on experience using Snowflake tools, SQL and Python is required Strong proficiency in GitHub for source control, branching strategy and reviews Knowledge of data integration patterns, data warehousing, and modern data architecture Strong analytical and communication skills, including the ability to analyze data, create meaningful insights, and present information clearly to stakeholders. Experience with object‑oriented programming and building with software engineering principles DevOps exposure, including CI/CD tools Understanding of Data Lake concepts Strong written and verbal communication skills are required, ability to collaborate, present, and report on findings Knowledge of Agile framework, Scrum methodologies and knowledge of tools used to support them Prior experience with government agencies and fraud detection systems is a plus Attention Candidates If you are selected for an interview, please be advised that Index Analytics LLC reserves the right to prohibit the use of artificial intelligence (AI) tools, including but not limited to AI-generated responses, real-time transcription, or automated assistance during the interview process. We value authentic interactions and the opportunity to engage directly with candidates. Any unauthorized use of AI may result in disqualification from consideration. We're dedicated to ensuring a safe and transparent recruitment process for all candidates and have implemented robust measures to protect your personal information. Please be aware that all employment-related communications will originate from a secure portal (@msg.paycomonline.com) or a corporate email address (@index-analytics.com). If you have any concerns, please don't hesitate to reach out to us at recruiting@index-analytics.com. Index Analytics provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training. Share job details to

Briscent Global LLC is seeking a motivated Data Engineer to join our team. This role is ideal for candidates who enjoy working with data, building reliable data pipelines, and transforming raw information into structured datasets that support analytics and business decisions. Responsibilities Design, develop, and maintain scalable data pipelines and ETL/ELT workflows. Collect, clean, transform, and validate data from multiple sources. Work with databases and data warehouses to organize and manage data efficiently. Develop SQL queries for data extraction, transformation, and analysis. Monitor data pipelines and troubleshoot data quality or processing issues. Collaborate with software engineers, analysts, and business teams. Document data processes, pipelines, and technical solutions. Support the development of dashboards, reporting systems, and analytics workflows. Required Skills Master's degree in Computer Science, Data Engineering, Information Technology, Engineering, or a related field. Strong understanding of SQL and relational databases. Basic knowledge of Python or another programming language. Understanding of ETL/ELT concepts and data pipeline development. Familiarity with cloud platforms such as AWS, Azure, or Google Cloud. Knowledge of data warehousing concepts is preferred. Strong analytical and problem-solving skills. Good communication and teamwork abilities. Preferred Skills Experience with Spark, Databricks, Airflow, Kafka, Snowflake, or BigQuery. Familiarity with cloud-based data engineering tools. Understanding of data modeling and database optimization. Internship, academic, or project experience in data engineering is a plus

Data Engineer

Delaware Nation Industries

Dahlgren, United States

DNI is seeking a highly qualified Data Engineer to support the Joint Warfare Analysis Center (JWAC) under Air Force JWAC IT Services (JITS) Task Order 2. The Data Engineer will design, implement, secure, monitor, and optimize cloud-native data engineering solutions that support data science, artificial intelligence/machine learning (AI/ML), agentic services, hosted models, and large language model (LLM) optimization. The role integrates data engineering, FinOps, Zero Trust security, and AI/ML infrastructure responsibilities within a single position. This position is expected to work onsite at JWAC in Dahlgren, Virginia, supporting a TS/SCI/SAP environment. Responsibilities Design, build, troubleshoot, and tune end-to-end cloud-native data engineering solutions using AWS platform and software services. Develop and administer data ingestion, ETL, integration, transformation, validation, publication, and lifecycle-management workflows. Integrate structured and unstructured data from databases, web services, message traffic, data dumps, documents, and other sources. Design data architectures and managed data stores that support analytics, feature engineering, model training, and real-time inference. Develop solutions using AWS services such as AWS Glue, Amazon Athena, Amazon Redshift, Amazon Kinesis, AWS Lake Formation, AWS Glue Data Catalog, Amazon RDS, Amazon Aurora, and Amazon DynamoDB. Create REST APIs and web services to expose data to JWAC-developed applications and analytical systems. Support AI/ML infrastructure, including model hosting, model-ready datasets, agentic workflow orchestration, retrieval-augmented generation (RAG), and LLM integration and optimization. Develop automation, monitoring, alerting, and self-healing capabilities using AWS-native tools such as Amazon CloudWatch and AWS CloudTrail. Implement data discovery and search capabilities using services such as Amazon OpenSearch Service, AWS Glue Data Catalog, and Amazon Kendra. Apply FinOps practices, including resource tagging, cost allocation, right-sizing, storage tiering, query optimization, budget monitoring, cost-per-workload analysis, and AI/LLM cost tracking. Implement DoD Zero Trust and NIST SP 800-53 Rev. 5 security controls across data engineering and AI service environments. Configure identity and access management, least-privilege access, encryption at rest and in transit, network segmentation, certificate management, and security monitoring. Support security assessments, compliance documentation, data-flow diagrams, control mappings, and authorization activities. Gather requirements, evaluate data sources, communicate technical recommendations, and document architecture, processes, costs, risks, and implementation decisions. Develop briefings, technical proposals, operating procedures, user documentation, training materials, and knowledge-transfer products. Collaborate with Government stakeholders, data scientists, analysts, cybersecurity personnel, cloud engineers, and other technical teams.

Data Engineer

MetaSense, Inc.

Dallas, TX

Looking for candidates regarding the following: POSITION Data Engineer LOCATION Dallas, TX DURATION 6 Months INTERVIEW TYPE on-site interview VISA RESTRICTIONS Must be able to convert without sponsorship REQUIRED SKILLS Required Skills: • Must have strong hands-on experience working with Databricks, SQL, and Python to build, support, and optimize enterprise data pipelines in production environments. • Proven expertise in writing advanced SQL queries using joins, window functions, CTEs, and performance tuning techniques to deliver high-quality and scalable data solutions. • Strong Python development experience using PySpark and pandas for data processing, automation, transformation, and pipeline development. • Hands-on experience designing and supporting Medallion Architecture , including Bronze, Silver, and Gold data layers to ensure trusted and well-governed analytical datasets. • Experience with data warehouse and database modeling, including dimensional modeling, normalized schemas, and designing structures that support reporting and analytics. • Strong understanding of data engineering best practices including data quality validation, monitoring, automated testing, troubleshooting, documentation, and production support. • Experience developing, maintaining, and optimizing data pipelines while performing root-cause analysis and resolving data issues in complex environments. • Ability to work closely with Data Engineers, Analysts, and business stakeholders to translate business requirements into scalable data solutions and trusted datasets. • Experience working with retail, wholesale distribution, supply chain, inventory, merchandising, pricing, logistics, or sales data domains is highly preferred. • Familiarity with modern data engineering tools and technologies such as Databricks, Delta Lake, Spark, Unity Catalog, Airflow, Azure Data Factory, Snowflake, Redshift, or BigQuery is a strong plus.

Data Engineer

Tabby

Georgia

Tabby creates financial freedom in the way people shop, earn and save by reshaping their relationship with money. Over 17 million users choose Tabby to stay in control of their spending and make the most out of their money. The company’s flagship offering allows shoppers to split their payments online and in-store with no interest or fees. Over 40,000 global brands and small businesses, including Amazon, Noon, IKEA, and SHEIN use Tabby to accelerate growth and gain loyal customers by offering easy and flexible payments online and in stores. Tabby generates over $10 billion in annual transaction volume for its partner brands and is the highest-rated, most-reviewed, largest, and fastest-growing FinTech in the GCC region. Tabby launched in 2019 and has since raised +$1 billion in equity and debt funding from global and regional investors, and is now valued at $4.5 billion. We are hiring a Data Engineer to join our DWH Team, who will help us create our corporate DWH using cloud technologies and best practices for data processing and storage. Key Responsibilities: DWH development for Business Users, Analysts and ML Engineers; Data synchronization between internal and external systems; Development tools for collecting data into DWH; Development EL / ELT / ETL pipelines; Integration new tools and practices for data governance and data quality; Costs optimization. Skills, Knowledge & Expertise: 3+ years of experience as a Data Engineer; DWH development and maintenance experience; Architecture: Kimball, Inmon, Medallion, Data Mesh; Data modeling: SCD forms, Normal forms, Star Schema, Data Vault; Python + best practice for Python; SQL + best practice for SQL; System design best practices; Familiar with tech stack as Airflow, dbt, BigQuery, Clickhouse, PostgreSQL, Docker, GitLab(CI/CD), GCP; Best practice for data processing and data storing. Bonus skills REST API / GRPC API / Message brokers & Queues; Experience on modern systems of data storing: Relational, MPP, NoSQL; Experience on Google Cloud Platform. What we offer: Full-time B2B contract Fully remote setup Up to 20% tax allowance 22 paid leave days annually Stock options (ESOP) in a fast-scaling, pre-IPO company Flexi benefits you can use for wellness, travel, or learning Work alongside a high-performing, international engineering team in a global fintech unicorn Relocation support is available to our hubs in Armenia, Georgia, Serbia, Poland and Spain, including flights, temporary accommodation, legal setup (if needed) Originally posted on Himalayas

Data Engineer

Tabby

Remote

Tabby creates financial freedom in the way people shop, earn and save by reshaping their relationship with money. Over 17 million users choose Tabby to stay in control of their spending and make the most out of their money. The company’s flagship offering allows shoppers to split their payments online and in-store with no interest or fees. Over 40,000 global brands and small businesses, including Amazon, Noon, IKEA, and SHEIN use Tabby to accelerate growth and gain loyal customers by offering easy and flexible payments online and in stores. Tabby generates over $10 billion in annual transaction volume for its partner brands and is the highest-rated, most-reviewed, largest, and fastest-growing FinTech in the GCC region. Tabby launched in 2019 and has since raised +$1 billion in equity and debt funding from global and regional investors, and is now valued at $4.5 billion. We are hiring a Data Engineer to join our DWH Team, who will help us create our corporate DWH using cloud technologies and best practices for data processing and storage. Key Responsibilities: DWH development for Business Users, Analysts and ML Engineers; Data synchronization between internal and external systems; Development tools for collecting data into DWH; Development EL / ELT / ETL pipelines; Integration new tools and practices for data governance and data quality; Costs optimization. Skills, Knowledge & Expertise: 3+ years of experience as a Data Engineer; DWH development and maintenance experience; Architecture: Kimball, Inmon, Medallion, Data Mesh; Data modeling: SCD forms, Normal forms, Star Schema, Data Vault; Python + best practice for Python; SQL + best practice for SQL; System design best practices; Familiar with tech stack as Airflow, dbt, BigQuery, Clickhouse, PostgreSQL, Docker, GitLab(CI/CD), GCP; Best practice for data processing and data storing. Bonus skills REST API / GRPC API / Message brokers & Queues; Experience on modern systems of data storing: Relational, MPP, NoSQL; Experience on Google Cloud Platform. What we offer: Full-time B2B contract Fully remote setup Up to 20% tax allowance 22 paid leave days annually Stock options (ESOP) in a fast-scaling, pre-IPO company Flexi benefits you can use for wellness, travel, or learning Work alongside a high-performing, international engineering team in a global fintech unicorn Relocation support is available to our hubs in Armenia, Georgia, Serbia, Poland and Spain, including flights, temporary accommodation, legal setup (if needed) Originally posted on Himalayas

Data Engineer

Trilon Group

Remote

Data Engineer Department: IT Employment Type: Full Time Location: Remote- USA Compensation: $116,000 - $155,000 / year Description Trilon is building a supercharged, technology-enabled future for our people and partners. The Data Engineer plays a key role in that mission by building and maintaining the data platform that powers Trilon’s enterprise analytics, automation, and AI capabilities. Reporting to the Vice President, Data & DevOps, this role is responsible for designing, developing, and maintaining scalable data integrations and transformations in Azure and Microsoft Fabric. The Data Engineer ensures that Trilon’s data platform delivers reliable, high-quality, and well-structured data to support business intelligence, operations, and innovation. This role serves as the primary custodian of Trilon’s integrated data model and is instrumental in developing a unified, extensible architecture that scales with continued acquisitions. The Data Engineer designs and builds secure Power BI semantic models for consumption by analysts and decision-makers, ensuring consistent and governed access to enterprise data. This role also partners closely with the AI and Innovation vTeam to prepare data for analytics, machine learning, and retrieval-augmented generation (RAG) applications. Key Responsibilities Data Platform Engineering and Maintenance Serve as the primary owner and technical steward of the Trilon enterprise data platform Design, develop, and maintain data pipelines and workflows using Azure Data Factory, Synapse, and Microsoft Fabric Build and manage data transformations, orchestration, and automation across structured, semi-structured, and unstructured data sources Ensure scalability, reliability, and performance of the data platform as Trilon continues to grow through acquisition Implement monitoring and alerting to proactively detect and resolve pipeline or data quality issues Data Integration and Modeling Develop and maintain integrations between Trilon’s enterprise systems, cloud services, and acquired partner environments Design and maintain a unified, scalable data model that harmonizes data across business systems Build secure, governed, and high-performance Power BI semantic models optimized for analytics and self-service reporting Collaborate with business analysts and data consumers to ensure data models support enterprise reporting needs and KPIs Partner with cybersecurity and infrastructure teams to ensure data models and access patterns meet compliance and governance standards Data Quality and Governance Implement validation and quality checks to ensure accuracy, completeness, and timeliness of enterprise data sets Maintain metadata, lineage, and documentation to promote transparency and reusability Define and enforce data quality and consistency standards across all integrated sources Collaborate with the Technology Asset Manager and Service Platform Manager to align system integrations and data governance Support data cataloging, discovery, and classification initiatives within Microsoft Purview or equivalent tools Automation, Optimization, and Resilience Develop automated frameworks for ingestion, transformation, and validation using Azure-native tools and pipelines Implement DevOps principles for data workflows including version control, testing, and deployment automation Optimize pipeline performance, resource utilization, and data freshness Build resilience and fault tolerance into data operations to ensure reliability and recovery Create reusable components and templates to streamline integration of new data sources and partner systems AI and Innovation Enablement Collaborate with the AI and Innovation vTeam to prepare and structure data for AI, ML, and RAG-based applications Develop and maintain data pipelines that support model training, evaluation, and fine-tuning Curate and transform unstructured data for retrieval, embedding, and vectorization within AI applications Ensure data readiness for generative AI tools, chat interfaces, and knowledge retrieval systems Stay informed of emerging AI data engineering trends and Microsoft Fabric AI integrations Collaboration and Cross-Domain Partnership Partner with application and infrastructure teams to ensure reliable and secure data exchange across systems Collaborate with business stakeholders and analysts to understand reporting needs and deliver usable data models Support integration engineers in onboarding new firms and ensuring their data aligns with Trilon’s enterprise model Work closely with cybersecurity and compliance teams to enforce data protection, retention, and access policies Provide documentation, architecture diagrams, and operational standards for the data platform and pipelines Skills, Knowledge and Expertise 7 or more years of experience in data engineering, data integration, or data platform development Strong hands-on experience with Azure Data Factory, Azure Synapse, Microsoft Fabric, and related Azure data services Proficiency in SQL, DAX, Power Query, and data modeling for Power BI Experience designing and maintaining Power BI semantic models, datasets, and row-level security configurations Familiarity with data governance, cataloging, and lineage management in tools like Microsoft Purview Experience building and optimizing cloud data pipelines with structured, semi-structured, and unstructured data Understanding of data preparation for AI and machine learning applications, including RAG architectures Exposure to engineering and geospatial data such as CAD, BIM, and GIS Strong analytical and problem-solving skills with a focus on scalability and performance Excellent collaboration and communication skills across technical and business audiences Bachelor’s degree in Computer Science, Data Engineering, or related field preferred Microsoft certifications such as Azure Data Engineer Associate or Fabric Analytics Engineer Associate are a plus May require occasional travel to Trilon offices or partner locations for integration or collaboration activities About Trilon Trilon was formed with the vision of building the next Top 20 infrastructure consulting firm in North America by bringing together some of the nation’s best infrastructure consulting firms, focused on delivering practical and sustainable infrastructure solutions. Trilon is backed by Alpine Investors, a PeopleFirst Private Equity Firm. Trilon currently comprises 5,500+ staff across the US. For more information, visit www.trilon.com. Pay Transparency The base salary range for this role is indicated in the posting. This range reflects the company’s good faith estimate of the compensation for this position at the time of posting. Final compensation will be determined based on factors such as experience, skills, qualifications, internal equity, and geographic location.

Data Engineer

Trilon Group

United States

Trilon is building a supercharged, technology-enabled future for our people and partners. The Data Engineer plays a key role in that mission by building and maintaining the data platform that powers Trilon’s enterprise analytics, automation, and AI capabilities. Reporting to the Vice President, Data & DevOps, this role is responsible for designing, developing, and maintaining scalable data integrations and transformations in Azure and Microsoft Fabric. The Data Engineer ensures that Trilon’s data platform delivers reliable, high-quality, and well-structured data to support business intelligence, operations, and innovation. This role serves as the primary custodian of Trilon’s integrated data model and is instrumental in developing a unified, extensible architecture that scales with continued acquisitions. The Data Engineer designs and builds secure Power BI semantic models for consumption by analysts and decision-makers, ensuring consistent and governed access to enterprise data. This role also partners closely with the AI and Innovation vTeam to prepare data for analytics, machine learning, and retrieval-augmented generation (RAG) applications. Key Responsibilities Data Platform Engineering and Maintenance Serve as the primary owner and technical steward of the Trilon enterprise data platform Design, develop, and maintain data pipelines and workflows using Azure Data Factory, Synapse, and Microsoft Fabric Build and manage data transformations, orchestration, and automation across structured, semi-structured, and unstructured data sources Ensure scalability, reliability, and performance of the data platform as Trilon continues to grow through acquisition Implement monitoring and alerting to proactively detect and resolve pipeline or data quality issues Data Integration and Modeling Develop and maintain integrations between Trilon’s enterprise systems, cloud services, and acquired partner environments Design and maintain a unified, scalable data model that harmonizes data across business systems Build secure, governed, and high-performance Power BI semantic models optimized for analytics and self-service reporting Collaborate with business analysts and data consumers to ensure data models support enterprise reporting needs and KPIs Partner with cybersecurity and infrastructure teams to ensure data models and access patterns meet compliance and governance standards Data Quality and Governance Implement validation and quality checks to ensure accuracy, completeness, and timeliness of enterprise data sets Maintain metadata, lineage, and documentation to promote transparency and reusability Define and enforce data quality and consistency standards across all integrated sources Collaborate with the Technology Asset Manager and Service Platform Manager to align system integrations and data governance Support data cataloging, discovery, and classification initiatives within Microsoft Purview or equivalent tools Automation, Optimization, and Resilience Develop automated frameworks for ingestion, transformation, and validation using Azure-native tools and pipelines Implement DevOps principles for data workflows including version control, testing, and deployment automation Optimize pipeline performance, resource utilization, and data freshness Build resilience and fault tolerance into data operations to ensure reliability and recovery Create reusable components and templates to streamline integration of new data sources and partner systems AI and Innovation Enablement Collaborate with the AI and Innovation vTeam to prepare and structure data for AI, ML, and RAG-based applications Develop and maintain data pipelines that support model training, evaluation, and fine-tuning Curate and transform unstructured data for retrieval, embedding, and vectorization within AI applications Ensure data readiness for generative AI tools, chat interfaces, and knowledge retrieval systems Stay informed of emerging AI data engineering trends and Microsoft Fabric AI integrations Collaboration and Cross-Domain Partnership Partner with application and infrastructure teams to ensure reliable and secure data exchange across systems Collaborate with business stakeholders and analysts to understand reporting needs and deliver usable data models Support integration engineers in onboarding new firms and ensuring their data aligns with Trilon’s enterprise model Work closely with cybersecurity and compliance teams to enforce data protection, retention, and access policies Provide documentation, architecture diagrams, and operational standards for the data platform and pipelines Skills, Knowledge and Expertise 7 or more years of experience in data engineering, data integration, or data platform development Strong hands-on experience with Azure Data Factory, Azure Synapse, Microsoft Fabric, and related Azure data services Proficiency in SQL, DAX, Power Query, and data modeling for Power BI Experience designing and maintaining Power BI semantic models, datasets, and row-level security configurations Familiarity with data governance, cataloging, and lineage management in tools like Microsoft Purview Experience building and optimizing cloud data pipelines with structured, semi-structured, and unstructured data Understanding of data preparation for AI and machine learning applications, including RAG architectures Exposure to engineering and geospatial data such as CAD, BIM, and GIS Strong analytical and problem-solving skills with a focus on scalability and performance Excellent collaboration and communication skills across technical and business audiences Bachelor’s degree in Computer Science, Data Engineering, or related field preferred Microsoft certifications such as Azure Data Engineer Associate or Fabric Analytics Engineer Associate are a plus May require occasional travel to Trilon offices or partner locations for integration or collaboration activities About Trilon Trilon was formed with the vision of building the next Top 20 infrastructure consulting firm in North America by bringing together some of the nation’s best infrastructure consulting firms, focused on delivering practical and sustainable infrastructure solutions. Trilon is backed by Alpine Investors, a PeopleFirst Private Equity Firm. Trilon currently comprises 5,500+ staff across the US. For more information, visit www.trilon.com. Pay Transparency The base salary range for this role is indicated in the posting. This range reflects the company’s good faith estimate of the compensation for this position at the time of posting. Final compensation will be determined based on factors such as experience, skills, qualifications, internal equity, and geographic location. Originally posted on Himalayas

Data Engineer This is a demanding role on a small, high-leverage team. You'll be one of a handful of people responsible for the data behind IPinfo's location and context products, working on ambiguous problems with messy inputs and owning your pipelines end to end - including understanding every line you ship. What you'll do Make sense of large, unfamiliar datasets sourced from publicly-contributed (and therefore inconsistent) datasets like OpenStreetMap and Overture, as well as error-prone device datasets with sometimes dozens of poorly-documented columns. Your job is to wade through these datasets, figure out what is going on, and extract a meaningful signal. Maintain and extend BigQuery data pipelines, writing efficient, transparent code that achieves complex data tasks while avoiding bloat and spaghetti. Work with particular expertise on Geospatial data, knowing the suite of BigQuery geospatial tools like the back of your hand, while dealing with the particular headaches and challenges that geospatial data poses. Occasionally working in python as well. Use AI tooling to move quickly while fully owning every line in your PRs. Communicate problems and solutions clearly using our internal issue-tracking platform; writing concise, reproducible records of the problem, the proposed solutions, and why you made the calls you did, so others can follow and build on them. Work occasionally on web-based dashboards to provide visibility to our data pipelines for data engineers as well as others at the company. What we're looking for Must have Advanced SQL - window functions, CTEs, query restructuring for performance, and an understanding of why a query is slow and how to fix it. BigQuery is a strong plus. Strong communication skills - you know how to talk and write about complex problems and data pipelines productively. A track record of turning messy, ambiguous data into reliable, interpretable signals, with the judgment to explain your calls. An internet record of significant experience as a data scientist or engineer, on Github, StackOverflow, in the academic literature or on a personal blog, or strong references to back up a track record on proprietary code bases. Clean-code discipline: you don't ship code without tests, code review, readable abstractions. You prefer subtractive solutions to additive solutions. Fast learning - comfort becoming productive in unfamiliar domains (internet measurement, geospatial reasoning, internal tooling) with little hand-holding. AI-assisted development paired with full ownership - you can read, debug, and defend everything the tools produce. Geospatial fundamentals: coordinate systems, spatial joins, containment, polygon operations. Nice to have Cloud tooling and workflow orchestration (CI/CD, Docker, Airflow, etc.). JavaScript and web dashboards (e.g. Retool, Mapbox, internal validation and visualization tooling). Exposure to the science of internet measurement: BGP/ASN, rDNS, RTT-based geolocation, CGNAT, mobile vs. fixed-line IP behavior, geofeeds. Strong Python for geospatial data work - comfortable with the data and geospatial stack (pandas, geopandas, shapely) and writing code that holds up in production, not just in a notebook.

Data Engineer

Foxconn Industrial Internet - FII

Houston, TX

Job Summary: Foxconn Houston has several Lighthouse Factory plants manufacturing servers and server cabinets. The company is hiring dedicated data engineers to ensure its data is accessible, secure, and efficient. This role collaborates with data analysts to create data pipelines for data from all kinds of sources within the manufacturing factory setting. The data engineer will create, maintain, and optimize ETL pipelines using Apache or other Big Data tools and Cicada, an internal ETL tool. This role will manage big data that are cross-factory, cross-business-units and cross-systems. Responsibilities: 10%, Analyzes user needs, system requirements and business processes. 40%, ETL/ manage data pipelines using Cicada. 40%, Processing real-time and batch Big Data. 10%, Design, create, maintain, update, manage and present Tableau Dashboards. Skills/Qualifications: Native speaking in Chinese Mandarin with ability to read the language and work in a professional setting. 3+ years of experience in data engineering, such as data warehousing and ETL pipeline design, development, and maintenance and optimization. Proficiency in ETL tool programing, debugging, maintenance, and monitoring to ensure data ingestion, cleansing, and loading. Experience with data warehouse modeling and standardization. Experience with backend API integration. Experience with system automated code CI/CD. Experience with system performance tuning and monitoring. Proficiency in SQL and Python. Proficiency in Hadoop, Kudu, Hive, Kafka, Spark and/or Flink. Proficiency in real-time and batch data processing on Big Data platforms Database development using Kudu 1.10.0 and higher, or Hive 2.1.1 and higher. RESTful API’s programming, at least 1 year of development experience. Advanced knowledge and experience with Linux (CentOS, RedHat, Ubuntu). Excellent communication, organization, and interpersonal skills. Experience leading data development projects. Excellent problem-solving skills with extreme attention to detail. Outstanding work ethic and commitment to individual and organizational success. Excellent analytical and advanced troubleshooting skills with end-users/clients. Ability to manage multiple tasks and projects, both independently and as part of a team. Demonstrated ability to learn new things and continuously drive process improvement. Plus/Desired: Familiar with electronics manufacturing industry domain know-how. Experience with Git Repositories (GITLAB) or JIRA. Experience with HTML5, CSS3, JavaScript and use front-end code debugging tools such as Chrome. Proficiency in Tableau or other data visualization tools. Educational Requirements: Bachelor’s degree in Data Engineering, Data Science, Data Management, Information Systems or related fields. Any software programming certifications are a plus.

Be Challenged and Make a Difference In a world of technology, people make the difference. We believe if we invest in great people, then great things will happen. At AnaVation, we provide unmatched value to our customers and employees through innovative solutions and an engaging culture. Description of Task to be Performed: AnaVation is seeking a Senior Data Engineer to join our growing Huntsville, Alabama work program. The selected candidate provides support large scale data engineering and migration activities for a major federal modernization program. This role is responsible for designing, developing, optimizing, and operating data pipelines supporting petabyte scale migration, transformation, and storage of structured and unstructured datasets. The Senior Data Engineer ensures data flows are reliable, repeatable, secure, and aligned to architectural standards required for transferring legacy datasets into modern cloud environments. Specific duties and responsibilities include: Design, build, and optimize scalable ETL/ELT pipelines for ingestion, transformation, and migration of large, multi-source datasets. Develop data models, schemas, mappings, and integration structures supporting legacy-to-cloud migration. Improve pipeline automation, performance, throughput, reliability, and fault tolerance. Lead data cleansing, normalization, enrichment, validation, and root-cause analysis for data quality issues. Partner with QA, Cloud, DevSecOps, Migration, and development teams to integrate and validate data workflows. Support AWS-based data engineering and ensure compliance with security, logging, auditing, and data-handling requirements. Mentor data engineers and participate in technical reviews, sprint activities, architecture discussions, and migration planning. Maintain pipeline diagrams, mapping specifications, data dictionaries, and other technical documentation. Track migration progress, pipeline performance, data quality, risks, and blockers, and support timely resolution. This position requires active Top Secret (TS) clearance and the ability to obtain SCI accesses with a CI polygraph. This position is on-site with our customer in Huntsville, Alabama, and cannot be supported remotely. Required Qualifications: Bachelor’s degree and 8+ years of experience in data engineering, ETL development, or large scale data operations. Hands on experience building pipelines for structured/unstructured data across enterprise environments. Strong proficiency in data modeling, transformation logic, and automation. Familiarity with cloud environments (AWS preferred), DevSecOps tooling, and scripting languages. Excellent analytical, documentation, and problem solving skills. Must be able to work full-time on-site at our customer location in Huntsville, Alabama. Active Top Secret (TS) clearance with eligibility for Sensitive Compartmented Information (SCI) and the ability to obtain a CI polygraph Preferred Qualifications: Experience with petabyte scale or multi system migration programs. Background supporting national security customers. Experience with CI/CD integration, automated testing pipelines, or micro service architectures. Advanced knowledge of ETL frameworks, distributed compute tools, or cloud native data services. Benefits Generous cost sharing for medical insurance for the employee and dependents 100% company paid dental insurance for employees and dependents 100% company paid long-term and short-term disability insurance 100% company paid vision insurance for employees and dependents 401k plan with generous match and 100% immediate vesting Competitive Pay Generous paid leave and holiday package Tuition and training reimbursement Life and AD&D Insurance About AnaVation AnaVation is the leader in solving the most complex technical challenges for collection and processing in the U.S. Federal Intelligence Community. We are a US owned company headquartered in Chantilly, Virginia. We deliver groundbreaking research with advanced software and systems engineering that provides an information advantage to contribute to the mission and operational success of our customers. We offer complex challenges, a top-notch work environment, and a world-class, collaborative team. If you want to grow your career and make a difference while doing it, AnaVation is the perfect fit for you! AnaVation is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.