Top Data Engineer Jobs

Design, develop, test, implement, and support cloud-based data solutions. Collaborate with Agile teams on full-stack and distributed systems, using Java/Scala/Python, RDBMS/NoSQL, data warehousing and streaming tools. Mentor engineers, perform unit tests and code reviews, and deliver performant, production-ready data platforms to support machine learning and customer-facing products.

Design, build, and maintain scalable data pipelines integrating diverse sources into analytics platforms. Own projects, standardize pipeline tooling, implement automated data tests, ensure security/PII handling, support on-call troubleshooting, and mentor team members to enable reliable, production-grade data delivery.

Lead design and implementation of scalable, HIPAA-compliant data pipelines and platforms for healthcare ML. Build ETL, orchestration, and tooling for processing EHR, claims, pharmacy, and bioinformatics data; collaborate with data scientists to produce modeling-ready datasets and ensure data quality, reliability, and operational excellence.

Design, develop, and deliver data solutions and database systems, maintain data pipelines, automate processes, and support internal teams with data infrastructures.

The Junior Data Engineer will work with data to enhance trading systems, support data warehouses, and collaborate on technical solutions with the team.

Build and maintain data quality scripts and automated validation workflows, support large data migrations to modern platforms including public cloud, triage and repair data quality issues, prepare datasets for client-facing materials, and ensure access to databases for business intelligence tools.

Design, build, and optimize distributed query solutions using Starburst/Trino. Enable secure, governed data access across cloud and on-premises sources, implement data federation and query optimization, support IAM and governance in a federal environment, develop backend services and CI/CD, and troubleshoot performance in cloud-native systems.

Design, build, monitor, and optimize large-scale ETL/ELT data pipelines and data architecture. Integrate data sources, support analysts and data scientists, automate processes, ensure reliable data delivery, and write maintainable code.

Lead design and delivery of complex, scalable data solutions and pipelines using SQL, Python, Synapse, Snowflake, dbt, and Fivetran. Ensure data quality, security, observability, and compliance (GDPR/HIPAA), mentor engineers, conduct architecture reviews, drive automation and cost/performance optimization, and partner with cross-functional teams to implement governance and data lineage.

Design, develop, and manage ETL workflows using Informatica PowerCenter; ensure data quality and reliable data flows; translate business needs into functional designs; write and optimize T-SQL/SQL, stored procedures and triggers; perform testing and manage production deployments with business teams.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

Design, develop, test, implement, and support cloud-based data solutions. Collaborate across Agile teams on distributed, streaming, and full-stack systems, mentor engineers, and perform unit tests and code reviews to deliver performant data products.

Design, develop, test, and support cloud-based data solutions and streaming systems. Collaborate with Agile teams, mentor engineers, and ensure performant, well-tested code for large-scale financial data workloads.

Lead and mentor engineering teams to design, develop, test, and deploy cloud-based data solutions. Build distributed, real-time and batch data pipelines using big data technologies, databases, and cloud warehouses. Collaborate with product managers and peers to deliver performant, production-ready systems and ensure code quality through testing and reviews.

Lead Data Engineer designing, developing, testing, and supporting cloud-based data solutions. Collaborate across Agile teams to build distributed, streaming, and batch data pipelines, mentor engineers, and optimize performance for data warehousing and machine learning use cases.

Design, build, and optimize ETL/ELT pipelines and data infrastructure using dbt, PostgreSQL, Azure streaming/storage, Apache Iceberg, and Trino. Containerize/orchestrate workloads, automate processes, support ML enablement on Azure, troubleshoot data quality, and mentor junior engineers.

The Data Engineer will manage data extraction pipelines, modernize data systems, implement monitoring tools, optimize workflows, and support compliance requirements using various tools and platforms.

Own operational support and optimization of enterprise data warehouse systems on AWS. Build and maintain scalable batch and streaming ETL/ELT pipelines, lead incident management and RCA, implement CI/CD and IaC, collaborate with cross-functional Agile teams, and provide shift-based on-call support while evaluating Generative AI integration opportunities.

Summer full-time (8-12 week) Data Engineer internship supporting data engineering, visualization, and insights tasks. Participate in agile meetings, complete trainings and assigned work, assist requirement gathering, and collaborate with teams to develop data solutions.

Migrate HiveQL and Python workflows from CDSW to Databricks, design and maintain ETL pipelines and databases, optimize data workflows on cloud platforms (AWS/Databricks), implement CI/CD, and collaborate with analytics teams to ensure scalable, high-quality data delivery supporting DoD stakeholders.

Design, build, and maintain batch and streaming data products, pipelines, and APIs. Acquire, transform, model, and expose data for analytics, reporting, and data science. Implement data quality, testing, CI/CD, and DevSecOps practices. Translate business requirements into technical stories and collaborate with architects, analysts, and stakeholders to meet governance and security needs.

Design, build, and maintain scalable GCP data pipelines using Airflow, Dataflow (Apache Beam), and BigQuery. Ingest and transform massive datasets, optimize pipeline performance, ensure data quality/security, and collaborate with data teams to troubleshoot and deliver reliable analytics solutions.

Design and build scalable data solutions, develop real-time data pipelines, maintain ETL processes, and promote effective development methodologies.

As a Data Engineer, you'll create and maintain data pipelines, optimize data architecture, and support analytics tools for performance insights.

The Data Engineer will manage and develop data warehousing solutions, implement ETL processes, and utilize SQL for data analysis and reporting. Experience in analytics tools and communication is essential.