Senior Data Engineer

Expression is seeking a Senior Data Engineer to build and integrate secure enterprise data services that enable AI and LLM capabilities for the Department of Homeland Security (DHS). This onsite role in Shirlington, VA focuses on governed integrations with authorized data platforms and on permission-aware data access for AI agents and retrieval-augmented generation (RAG) workflows.

What you’ll do

• Design, develop, and maintain secure enterprise data integrations that connect Government-approved data platforms with AI applications and agentic AI workflows within the existing AI environment.
• Develop and integrate APIs, data connectors, and retrieval services for Palantir, Databricks, Elasticsearch, and other authorized enterprise data sources.
• Implement data access and retrieval capabilities for structured, semi-structured, and unstructured data, including records, documents, relationships, and analytical data products.
• Design and maintain schema mappings, data transformations, and context-preparation processes that support RAG, intelligent search, AI-assisted document generation, and source-grounded analytical workflows.
• Implement secure, permission-aware data access controls, including authentication, authorization, identity propagation, case-purpose restrictions, and source-level permissions.
• Ensure data provenance, lineage, and traceability by preserving source identifiers, timestamps, metadata, access restrictions, and document references across retrieval and AI processing.
• Build data validation, quality checks, and consistency controls to detect missing, stale, malformed, conflicting, or unauthorized records before downstream AI consumption.
• Optimize retrieval and API performance for query efficiency, response latency, and reliable access to enterprise data services.
• Collaborate with AI engineers to integrate authorized data into LLM and RAG workflows, ensuring outputs can be traced back to supporting source records and comply with access controls.
• Create automated unit, integration, and regression tests for connectors, APIs, schema mappings, data quality, and authorization boundaries.
• Implement secure error handling, audit logging, and observability to monitor performance, troubleshoot failures, and support operational reliability.
• Support controlled data synchronization and approved write-back operations where authorized, including input validation, human approval requirements, and safeguards against duplicate or unauthorized updates.
• Coordinate with enterprise platform owners, cybersecurity teams, and Government stakeholders to define interface specifications, resolve integration challenges, and maintain compliance with approved data governance requirements.
• Produce and maintain interface control documents, data-flow diagrams, schema mappings, API specifications, test results, operational runbooks, and technical documentation.
• Support CI/CD integration, configuration management, software releases, and regression testing as schemas, interfaces, and access requirements evolve.
• Participate in technical design reviews, code reviews, engineering planning, and cross-functional troubleshooting.
• Assist with technical demonstrations, prototype evaluations, Government acceptance testing, and operational pilot deployments.

Key qualifications

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Software Engineering, Data Science, or a related technical field, or equivalent relevant professional experience.
• 7+ years of professional experience in data engineering, software engineering, or enterprise data integration, including 3+ years building enterprise data pipelines, APIs, or governed data services.
• Strong skills in SQL and Python for querying, transformation, API integration, scripting, debugging, and automated testing.
• Proven experience designing and maintaining enterprise data integrations, including RESTful APIs, data connectors, schema mappings, and secure data exchange.
• Hands-on integration experience with at least one of: Palantir, Databricks, or Elasticsearch.
• Experience working with structured, semi-structured, and unstructured enterprise data, including data modeling, schema management, transformation, and retrieval optimization.
• Demonstrated experience implementing secure, permission-aware data access including authentication, authorization, identity propagation, sensitive-data handling, and source-level restrictions.
• Experience implementing data quality, validation, lineage, and traceability controls.
• Experience building data retrieval services or pipelines for analytics, intelligent search, AI applications, and RAG workflows.
• Ability to troubleshoot complex integration issues such as API failures, schema inconsistencies, query performance, authorization errors, and data quality problems.
• Experience with modern delivery practices including Git, code reviews, CI/CD, automated testing, and configuration management.
• Ability to translate technical and data governance requirements into secure integration designs, data contracts, test cases, and engineering documentation.
• Strong written and verbal communication skills for collaboration with AI engineers, developers, enterprise platform owners, and Government stakeholders.

Technologies

• SQL, Python, RESTful APIs, Git, CI/CD, Palantir, Databricks, Elasticsearch, RAG, LLM, AI

Benefits

• 401k matching
• PPO and HDHP medical/dental/vision insurance
• Education reimbursement up to $10,000/yr
• Complimentary life insurance
• Generous PTO and 11 days of holiday leave
• Commuter Benefits Plan

Security clearance

• Secret clearance required with eligibility for TS/SCI.

Location and compensation

• Location: Shirlington, VA (onsite)
• Salary: USD 180,000 - 200,000 per yearly

Preferred qualifications

• Hands-on integration experience with two or more of Palantir, Databricks, and Elasticsearch.
• Experience with Palantir data objects, relationships, APIs, or governed data-access capabilities.
• Experience with Databricks data products, SQL query services, data governance, lineage, or managed analytical datasets.
• Experience with Elasticsearch query APIs, index/alias management, document retrieval, and field-level access restrictions.
• Experience implementing RAG data pipelines, semantic or vector retrieval, document parsing, embeddings, and context preparation for LLM-powered applications.
• Experience supporting AI/ML or generative AI applications requiring secure retrieval of enterprise data, source attribution, and permission-aware context assembly.
• Experience with cloud-native data engineering and containerized applications using AWS, Azure, Docker, Kubernetes, or comparable technologies.
• Familiarity with Infrastructure as Code, DevSecOps practices, and automated deployment pipelines.
• Experience implementing controlled data synchronization, incremental updates, audit logging, and approved write-back operations across enterprise systems.
• Experience supporting Federal Government, Department of Defense, Intelligence Community, Department of Homeland Security, or similarly regulated data environments.
• Familiarity with Government cybersecurity, privacy, data governance, access control, and software authorization requirements.
• Experience supporting technical demonstrations, Government acceptance testing, operational pilots, or production data integration sustainment.