Top Data Engineer Jobs

Design, build, and maintain scalable data pipelines and architecture to support analytics and applications. Develop datasets and analytics tools, automate data workflows, ensure security/privacy of healthcare data, troubleshoot data issues, and partner with Product, Engineering, and business stakeholders to deliver data solutions.

Design, implement, and optimize enterprise data architecture and management for healthcare analytics. Lead data solutions using Microsoft Fabric and Power BI, ensure data governance, integrate imaging and EMR systems, troubleshoot ETL/SSIS, manage projects, mentor staff, and ensure HIPAA-compliant data practices.

Design, build, deploy, and support data integration and ETL pipelines on a Spark/Databricks and AWS-based platform. Lead requirements gathering, author technical designs and test plans, implement BI/analytics solutions, follow DevOps and agile practices, and improve integration architecture and operational procedures.

Design, develop, and maintain databases and scalable data pipelines. Build stored procedures, triggers, and ETL processes; perform testing, tuning, security, and data quality work. Collaborate with developers and stakeholders, document architecture, review code, and support reporting and integrations to enable restaurant and customer-facing systems.

Design, build, and maintain ETL pipelines, databases, and data models to process healthcare claims and related data. Ensure data quality, analyze claims data for trends, and produce reports and visualizations for nontechnical stakeholders. Collaborate with policy and analytics teams to translate requirements into data solutions and improve data infrastructure and analytics capabilities.

Design, build, and maintain batch and streaming data pipelines; ingest, transform, and optimize data for analytics and BI; ensure data quality, reliability, and performance; implement monitoring/alerting; support MLOps and analytics workloads; collaborate with data scientists and BI teams; document AI systems and RAG/Cortex-based solutions.

Design, build, support, and troubleshoot data pipelines, integrations, and data warehouses. Collaborate with cross-functional teams, recommend tools and frameworks, ensure data governance, and mentor junior data engineers.

Design, build, operationalize, and maintain enterprise-scale data applications and scalable ETL/ELT pipelines. Develop and troubleshoot Palantir Foundry transformations, ontology objects, and logs. Collaborate with cross-functional teams to convert structured and unstructured data for analytics, monitoring, and platform operations.

Design, develop, and maintain scalable data pipelines, warehouses, and stores. Build ETL/ELT workflows, process structured and unstructured data with SQL and Python, validate databases, and support data platform scaling, monitoring, and operations for mission-driven clients.

Design, build, and own Sardine's internal data platform and billing infrastructure. Implement and maintain ETL/ELT pipelines, warehouse partitioning, access controls, and data governance. Partner with stakeholders to define KPIs, produce dashboards, and ensure data quality for executive, GTM, product, and finance teams.

Lead hands-on data engineering and architecture for a classified on-prem Analytics Core: build ETL/ELT pipelines, clean and model 30 years of multi-modal and geospatial data, integrate ESRI spatial data, establish AI/ML feature standards, enforce DoD-aligned governance, and mentor transitioning staff to operationalize the solution.

Design, build, operate, and maintain production ETL/ELT pipelines, integrations, and curated datasets across Salesforce, Deltek, Autodesk, Azure, and Microsoft Fabric. Implement data models, orchestration, API-first services, monitoring, data quality, governance, and support AI/ML and BI initiatives while partnering with stakeholders to ensure secure, reliable data delivery.

Design, develop, and optimize data warehousing and ETL/ELT solutions on Microsoft SQL Server and cloud platforms. Perform data profiling, cleansing, dimensional modeling (Kimball), and performance tuning. Build semantic models and Power BI/Microsoft Fabric solutions, advise on architecture, mentor teammates, assist in pre-sales/scoping, and promote BI best practices across clients.

Design, build, operate, and maintain production ETL/ELT pipelines, integrations, and curated datasets across enterprise systems (Salesforce, Deltek, Autodesk, Azure, Microsoft Fabric). Implement data models, orchestration, API-first services, monitoring, data quality, lineage, and governance to support BI, reporting, AI/ML, and business decision-making. Collaborate with analytics, IT/security, and business teams to ensure secure, reliable data delivery.

The Senior Lead Data Engineer designs and develops technical solutions, leads a team of developers, and utilizes big data and cloud technologies to deliver robust solutions for Capital One.

Lead cross-functional Agile teams to design, build, test, and support cloud-based data solutions. Develop full-stack data engineering systems using Java/Scala/Python, RDBMS and NoSQL, Redshift/Snowflake, and distributed tools (Hadoop, Spark, Kafka). Mentor engineers, perform code reviews and unit testing, and collaborate with product managers to deliver scalable, performant data products.

As a Lead Data Engineer, you will collaborate in Agile teams to design and implement financial data solutions, utilizing extensive programming and cloud technologies.

As a Senior Lead Data Engineer, you will design, develop, and support data solutions, optimize systems, and collaborate within Agile teams to leverage technology for business transformations.

Lead a team of engineers to design and implement data solutions using cloud technologies, optimizing data pipelines and collaborating with Agile teams to deliver impactful data-driven products.

Lead Data Engineer role focused on building data solutions, collaborating across Agile teams, utilizing big data and cloud technologies, and mentoring team members.

Design, build, and operate large-scale data platforms and Spark/PySpark pipelines. Enable data integration, modeling, quality, and observability. Build MCP servers and AI-augmented tooling, mentor engineers, and lead cross-functional projects to deliver reliable data products.

Lead Data Engineer designs, develops, tests, and supports cloud-based data solutions. Collaborates with Agile teams, mentors engineers, implements big data and streaming systems, and optimizes code for performance to deliver data-driven products.

Lead and mentor data engineering teams to design, build, test, and support cloud-based, full-stack data solutions. Work with big data, streaming, and data warehousing technologies (Redshift/Snowflake), collaborate with product managers, and ensure high-quality, performant code and systems.

Responsible for building data models, developing ELT pipelines, implementing data quality checks, and utilizing best practices in data engineering and healthcare analytics.

The Lead Data Engineer will design, implement, and maintain data pipelines for mission-relevant data, ensuring compliance with security frameworks and optimizing data accessibility and interoperability across mission systems.