Data Engineer, Lead

Design enterprise data architectures and build the pipelines, knowledge indexes, and retrieval services that ground AI applications in authorized information. This role helps ensure data and retrieval are reliable, governed, and dependable, with close partnership between data and AI Engineering to improve retrieval behavior and response quality.

Work model: Onsite in McLean, VA.

Compensation: $77,600 to $176,000 per year (annualized USD). Education: Bachelor’s degree required.

What you’ll do

• Design data architectures and build pipelines, knowledge indexes, and retrieval services that enable agents to use authorized enterprise information.
• Partner with source-system owners and engineering teams to define data contracts, integrate structured and unstructured sources, and maintain permissions, lineage, quality, and freshness.
• Own the reliability of data and retrieval services, partnering with AI Engineering on application retrieval behavior and response quality.
• Contribute to architecture and governance decisions (architecture-focused roles) or to pipeline, connector, and service implementation (engineering-focused roles).
• Implement and maintain ingestion, transformation, indexing, synchronization, and retrieval services.

What you’ll need

• Experience designing or implementing enterprise data platforms, lakehouse architectures, and integrations for structured and unstructured data.
• Proficiency with SQL and Python, including developing, testing, and operating ETL or ELT pipelines.
• Experience defining data models and schemas, data contracts, APIs, and access patterns that support downstream applications.
• Experience with data governance including source permissions, lineage, quality controls, and monitoring for freshness and availability.
• Knowledge of retrieval-augmented generation (RAG), embeddings, vector indexes, and semantic or hybrid search.
• Ability to troubleshoot ingestion and retrieval failures and assess relevance, latency, scalability, and data quality.
• Ability to translate enterprise requirements into architecture decisions, integration standards, and governance patterns.
• Ability to implement and maintain ingestion, transformation, indexing, synchronization, and retrieval services.
• Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements.
• Bachelor’s degree.

Technologies

• SQL, Python
• ETL, ELT

Nice to have

• Experience with Databricks, Spark, Delta Lake, vector databases, or comparable platforms.
• Experience with permission-aware retrieval, metadata enrichment, incremental ingestion, or knowledge engineering.
• Experience delivering reusable customer connectors and data services for production AI applications.

Benefits

• Health, life, disability, financial, and retirement benefits
• Paid leave
• Professional development
• Tuition assistance
• Work-life programs
• Dependent care
• Recognition awards program

Vetting and interview requirements

• Selected applicants will be subject to a government investigation and may need to meet eligibility requirements of the U.S. government client.
• Applicants are expected to be on camera during interviews and assessments.
• Identity verification may include taking your picture to prevent fraud.
• Use of AI or other tools to assist with responses during interviews is prohibited unless permission is explicitly provided.

Non-discrimination: All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran, or any other status protected by applicable federal, state, local, or international law.