Top Senior Data Engineer Jobs in Richmond, VA

The Data Engineer is responsible for designing data workflows and pipelines, implementing systems engineering principles, and deploying data streaming technologies while ensuring compliance with industry regulations and best practices.

Forward-deployed senior data engineer who deploys, hardens, integrates, and operates a data platform (lakehouse, streaming, governance) in DoD environments. Build pipelines across classification boundaries, produce accreditation evidence (STIG/cATO/FIPS), run day-2 operations, train mission teams, and mentor junior FDEs while feeding field feedback into product improvements.

Lead large-scale migration of document-heavy legacy systems into cloud, convert unstructured documents to analytics-ready data, build MuleSoft integrations and APIs, apply DataWeave transformations, ensure data quality, lineage, governance, and support Salesforce Data 360 implementation and cutover in Agile teams.

Owner of data platform modernization: design and migrate legacy systems to Kimball-style dimensional models and star schemas; build reliable production data pipelines; enforce data hygiene and validation; champion dbt best practices; mentor junior engineers; collaborate with analysts and stakeholders to ensure scalable, well-documented data models and platform observability.

The Senior Data Engineer will design and maintain data pipelines, provide technical leadership, and work with cloud platforms like AWS, Azure, and GCP.

Design and maintain data pipelines using cloud technologies. Provide technical leadership, implement data engineering solutions, and mentor engineers. Collaborate with stakeholders and stay updated on cloud advancements.

Design, implement, and maintain cloud-based data pipelines and architectures across AWS/Azure/GCP. Advise clients on best practices, partner with stakeholders to translate requirements, provide technical leadership, and mentor engineers while leveraging ETL/orchestration tools, data warehouses/lakes, databases, and programming languages for scalable data solutions.

The Senior Bioinformatics Data Engineer will build data pipelines, implement clinical data ingestion, and optimize platform infrastructure while ensuring data quality and compliance with legal standards.

Design, build, and maintain Keboola-based data pipelines integrating multiple business systems to deliver accurate, scalable data for supply chain, logistics, and transportation analytics; collaborate with analysts and engineers; support documentation, governance, and pipeline automation.

Design and build end-to-end geospatial data systems: ingest and process satellite imagery into columnar/chunked stores, expose results via GraphQL/REST and FastAPI, build Next.js/React dashboards, automate with IaC and CI/CD, orchestrate pipelines with Prefect, optimize petabyte-scale I/O, and lead hiring, mentoring, and engineering best practices.

Design, build, and maintain scalable data models and pipelines using Python and SQL. Collaborate with product and SMEs to create analytics-ready healthcare datasets, maintain data engineering systems, document solutions, and iterate based on product feedback.

Seeking a Senior BODS Developer to develop and maintain complex BODS processes for data transformation. The role includes improving data quality using Information Steward and GAC/URAC techniques, collaborating with teams, creating documentation, and mentoring others.

Design, build, and maintain Scala-based ETL and streaming data pipelines, APIs, and data microservices in Azure. Optimize LLM fine-tuning and RAG workflows, support DevOps/CI-CD practices, document standards, mentor engineers, and manage data ingestion frameworks for analytics and partner integrations.

Lead development and ownership of end-to-end data pipelines and platform tools. Build and optimize ingestion, transform data with dbt and Jinja, implement monitoring/alerting, manage deployments and CI/CD, and create self-service analytics applications and internal tooling.

Lead design, operation, and reliability of production data pipelines in a multi-terabyte Snowflake environment. Translate client requirements into dimensional models, debug and remediate pipeline failures, evolve the data mart for event-driven and AI workflows, and improve pipeline trustworthiness via testing, CI/CD, audit logging, and documentation.

Design, build, and maintain scalable data pipelines and models; collaborate with analysts and data scientists to provision prepared datasets; implement data quality, governance and monitoring; recommend technologies; lead root-cause analysis, code reviews and testing; mentor teammates and support production data environments.

Own end-to-end client data migrations: reverse-engineer legacy ETL, design and build Airflow DAGs and Spark jobs, validate and reconcile data at scale, document architecture and decisions, and coordinate cross-functional teams through go-live and hypercare.

The Senior Data Engineer will develop data engineering solutions, manage ETL workflows, and establish a new data practice while collaborating with stakeholders.

The Lead Data Platform Engineer will design and build Virtuous's data platform, ensuring it is secure, scalable, and AI-ready. Responsibilities include architecting access controls, optimizing performance, and enabling self-service analytics while maintaining governance and compliance standards.

The Senior Data Engineer will design and scale cloud-based data platforms, ensuring quality and performance while collaborating with cross-functional teams to deliver actionable data solutions.

Lead design, build, and support of cloud-based ETL, data warehousing, and reporting solutions. Develop/optimize ETL pipelines, data models, and queries; deploy containerized services on Kubernetes; automate workflows; mentor teammates; collaborate with architects, data scientists, and stakeholders to deliver scalable analytics and reporting products.

Design and scale data infrastructure, ensure data quality and governance, collaborate with teams on data products, and modernize practices.

Design and maintain data systems for business-critical insights, connect data across platforms, build ETLs, and support business data decisions.

The Data Engineer builds and maintains data infrastructure, develops data pipelines, ensures data quality, and collaborates with teams for insights.

The Senior Data Analytics Engineer will develop data pipelines, support data-driven decision-making, collaborate with stakeholders, and improve data quality and processes.