Data Engineer

Leidos • Washington, DC

23h • $87,100 - $157,450 • Remote

About The Position

Leidos is seeking a Data Engineer to support the Department of Veterans Affairs (VA) Summit Advanced Tooling, Lakehouse, and Artificial Intelligence Services (ATLAS) program. The role works with VA customers, data owners, analysts, and platform teams to onboard data sources and deliver reliable, analytics-ready data products using approved Summit engineering and governance patterns. The position is contingent upon contract award.

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

Requirements

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline and 8+ 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 ability to independently implement data pipelines using established design and deployment patterns.
• Ability to obtain and maintain the required VA Public Trust suitability determination (Tier 2/Moderate Risk).

Nice To Haves

• 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 working directly with customer teams to translate data requirements into accepted, production-ready datasets.
• 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.

Responsibilities

• Assess customer data and analytics requirements with product owners, business analysts, and data stewards, and translate needs into scoped ingestion and transformation tasks.
• Develop, configure, test, and maintain batch or event-driven data pipelines for new and migrated data sources using approved platform patterns.
• Build customer-focused transformations, semantic views, and consumption-ready datasets for reporting, analytics, and data science.
• Perform source-to-target reconciliation, freshness checks, data quality validation, and defect remediation; document evidence for customer acceptance.
• Implement approved access, metadata, lineage, and security requirements in coordination with governance and security teams.
• Monitor pipeline health and performance, troubleshoot failed loads and data discrepancies, and support production incidents and corrective actions.
• Document pipeline configurations, dependencies, runbooks, and handoffs; contribute improvements to reusable templates and automation.
• Coordinate customer onboarding and technical handover with Summit platform and customer enablement teams.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior