Senior Data Engineer

Description

This position is contingent upon contract award.

Leidos is seeking a Senior Data Engineer to support the Department of Veterans Affairs (VA) Summit Advanced Tooling, Lakehouse, and Artificial Intelligence Services (ATLAS) program.

Remote work within CONUS is subject to VA security and system-access requirements. Must support Eastern Time collaboration and applicable production coverage. Occasional after-hours or weekend support may be required for critical outages or planned maintenance.

This role focuses on engineering reusable ingestion, transformation, quality, and automation capabilities that improve the scalability, reliability, and efficiency of the Summit Data Platform across customer workgroups.

Primary Responsibilities

• Design and implement reusable data ingestion, transformation, orchestration, and validation frameworks aligned with the Summit product roadmap and approved enterprise architecture.
• Lead engineering of shared pipeline templates, data-quality gates, lineage instrumentation, and automated deployment or recovery patterns that reduce manual effort across workgroups.
• Optimize cloud data processing, partitioning, performance, reliability, and cost; establish practical technical measures and tuning recommendations.
• Provide technical guidance on complex data integration, source parity, semantic modeling, and federated query capabilities; collaborate with architecture and governance leads.
• Integrate automated testing, observability, CI/CD, infrastructure-as-code where appropriate, and secure access controls into production data engineering workflows.
• Troubleshoot complex cross-platform failures and data-quality issues; coordinate root-cause analysis, remediation, rollback, and operational readiness.
• Maintain reusable design documentation, standards implementation guidance, runbooks, and technical decision records.
• Mentor engineers and coordinate with customer-requested engineering teams to promote adoption and reuse of common capabilities.

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline and 10+ years of relevant experience, including demonstrated expertise designing and implementing complex data engineering solutions.
• Hands-on experience developing and troubleshooting production data ingestion, ETL/ELT, transformation, and validation pipelines using SQL and Python.
• Experience with cloud-based data platforms and services in Microsoft Azure, AWS, or Google Cloud; understanding of storage, orchestration, and secure data access.
• Experience with data modeling, source-to-target reconciliation, data quality testing, and pipeline monitoring or incident troubleshooting.
• Ability to document technical designs, data flows, dependencies, and operational procedures and collaborate with engineers, analysts, and data owners.
• Demonstrated experience designing reusable production data engineering frameworks or shared services and independently resolving complex integration and performance issues.
• Experience improving data engineering delivery through automation, testing, CI/CD, or standardized deployment patterns.
• Ability to obtain and maintain the required VA Public Trust suitability determination (Tier 2/Moderate Risk).

• Highly Preferred: Direct, hands-on experience supporting the VA Summit Data Platform is highly preferred; experience with other VA enterprise data and analytics environments is also valuable.
• Experience with production-scale Spark/Databricks or Delta Lake processing and platform-wide performance or cost optimization.
• Experience mentoring engineers or coordinating shared engineering capabilities across multiple delivery teams.
• Hands-on Microsoft Azure data engineering experience, including Azure Data Factory, Azure Data Lake Storage, Azure Databricks, Spark, or comparable services.
• Familiarity with Delta Lake/lakehouse architectures, data catalogs and lineage, and governance tools such as Collibra, Immuta, or Starburst.
• Experience supporting federal IT systems and complying with security, privacy, and data-access requirements.
• Experience with Agile delivery and relevant cloud/data engineering certifications. such as Microsoft Certified: Azure Data Engineer Associate, Databricks Certified Data Engineer Professional, AWS Certified Data Engineer - Associate, or equivalent.