[Hiring] Data Engineer/Architect @Leidos

Role Description

Leidos has an exciting opportunity for an experienced Data Engineer/Architect to support the design of a new data foundation. This foundation will support generative AI applications, including retrieval-augmented generation (RAG), and enable analysis of diverse data sets. Looking for an engineer with strong architectural and hands-on development skills who can define the foundation (tools, schemas, and ontologies) and document that definition so that software engineers can implement, and management can understand the capabilities that the foundation can support.

This role is open to candidates across a range of experience levels. The scope of the position and corresponding compensation will be aligned with the selected candidate’s background and expertise.

Qualifications

• Bachelor’s degree with 8+ or 12+ years of experience in a Science, Engineering, or Technology field or a Master’s degree with 6+ or 10+ years of experience in a Science, Engineering, or Technology field. Additional experience may be considered in lieu of a degree.
• US citizenship; Ability to obtain a Top Secret security clearance in DISS.
• 5+ years of experience with design and development of systems to analyze structured and unstructured large data sets from disparate sources.
• 5+ years of experience with principals associated with AI applications, including retrieval-augmented generation (RAG).
• Ability to develop tools, algorithms and queries to improve business performance.
• Ability to develop new technical solutions, including hands-on Python or JavaScript development, to achieve project goals.
• Ability to develop intelligent systems that analyze data, learn from patterns, predict outcomes, and make informed decisions autonomously.
• Strong verbal and written communication skills and ability to communicate data engineering and architectural concepts to non-technical audience.
• Experience working directly with product owners.

Requirements

• Design and implementation of big data systems, ETL pipelines and Data Lakes / Lakehouse / Meshes.
• Design and implementation of schema and ontologies.
• Design and implementation of data foundation to support generative AI applications, including retrieval-augmented generation (RAG), and business analytics.
• Design and implementation of row/cell level data access control.
• Hands-on software development using Python and/or JavaScript to support data integration and application functionality.
• Documentation of data definitions and designs.

Preferred Qualifications

• Experience integrating and/or operating: Dagster, PostgresSQL, Alembic, pgvector.
• Experience with digital Engineering (SysML).
• Experience with generative AI applications, including RAG, embeddings, and vector search.
• Experience with operational support to data foundation and devOps.
• Familiar with Medallion style architecture.
• Current Secret clearance in DISS.

Company Description

Please be advised that during the interview, you will be required to keep your camera on, and your interviewer will be taking your picture for identification purposes if an offer letter is extended to you.

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

Original Posting: October 21, 2026

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range: Pay Range $107,900.00 - $195,050.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.