{"id":4047891,"url":"https://alion.io/job/expression-networks-senior-data-engineer","title":"Senior Data Engineer","company":{"id":24004,"name":"Expression Networks","domain":"expr.ai","url":"https://alion.io/company/expr","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Breezy","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ElasticSearch","optional":false},{"name":"Git","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"Agile","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"Embeddings","optional":true},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-11-11T00:42:58Z","employer_posted_date":"2026-11-11","last_verified_at":"2026-11-11T00:44:01Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Expression is seeking an experienced Senior Data Engineer to design, develop, and integrate secure enterprise data services supporting advanced Artificial Intelligence (AI) and Large Language Model (LLM) capabilities for the Department of Homeland Security (DHS).\nThis position will support the development of secure, mission-focused AI applications within the Government's existing AI environment. The Senior Data Engineer will be responsible for implementing governed data integrations with enterprise platforms, including Palantir, Databricks, and Elasticsearch, enabling AI agents and retrieval-augmented generation (RAG) workflows to securely access, process, and reference authorized information.\nThe ideal candidate is a hands-on data engineer with extensive experience in enterprise data integration, API development, data modeling, and secure data access. You are comfortable working across complex data ecosystems, developing scalable integration services, troubleshooting data quality and performance issues, and collaborating with AI engineers to deliver reliable, source-grounded AI applications.\nThis role requires strong SQL and Python development skills, experience integrating structured and unstructured enterprise data, and an understanding of data governance, access controls, and data lineage. You will work closely with AI architects, AI engineers, platform owners, and Government stakeholders to ensure AI applications have reliable, permission-aware access to trusted enterprise data.\nSecurity Clearance: Secret clearance required with eligibility for TS/SCI.\nLocation: Shirlington, VA\nKey Responsibilities\nDesign, develop, and maintain secure enterprise data integrations connecting Government-approved data platforms with AI applications and agentic AI workflows within the existing AI environment.\nDevelop and integrate APIs, data connectors, and retrieval services for Palantir, Databricks, Elasticsearch, and other authorized enterprise data sources.\nImplement data access and retrieval capabilities supporting structured, semi-structured, and unstructured data, including records, documents, relationships, and analytical data products.\nDesign and maintain schema mappings, data transformations, and context-preparation processes to support retrieval-augmented generation (RAG), intelligent search, AI-assisted document generation, and source-grounded analytical workflows.\nImplement secure, permission-aware data access controls, including authentication, authorization, identity propagation, case-purpose restrictions, and source-level permissions.\nEnsure data provenance, lineage, and traceability by preserving source identifiers, timestamps, metadata, access restrictions, and document references throughout data retrieval and AI processing workflows.\nDevelop data validation, quality checks, and consistency controls to identify missing, stale, malformed, conflicting, or unauthorized records before they are consumed by downstream AI applications.\nOptimize data retrieval and API performance, including query efficiency, response latency, and reliable access to enterprise data services.\nCollaborate with AI engineers to integrate authorized data into LLM and RAG workflows, ensuring generated outputs can be traced to supporting source records and comply with established access controls.\nDesign and implement automated unit, integration, and regression tests for data connectors, APIs, schema mappings, data quality, and authorization boundaries.\nImplement secure error handling, audit logging, and observability to monitor data integration performance, troubleshoot failures, and support operational reliability.\nSupport controlled data synchronization and approved write-back operations where authorized, including input validation, human approval requirements, and safeguards against duplicate or unauthorized updates.\nCollaborate with enterprise platform owners, cybersecurity teams, and Government stakeholders to define interface specifications, resolve integration challenges, and maintain compliance with approved data governance requirements.\nProduce and maintain interface control documents, data-flow diagrams, schema mappings, API specifications, test results, operational runbooks, and technical documentation.\nSupport CI/CD integration, configuration management, software releases, and regression testing as enterprise data schemas, interfaces, or access requirements evolve.\nParticipate in technical design reviews, code reviews, engineering planning, and cross-functional troubleshooting activities.\nSupport technical demonstrations, prototype evaluations, Government acceptance testing, and operational pilot deployments.\nRequired Qualifications\nBachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, Data Science, or a related technical field, or equivalent relevant professional experience.\n7+ years of professional experience in data engineering, software engineering, or enterprise data integration, including 3+ years of hands-on experience developing enterprise data pipelines, APIs, or governed data services.\nStrong SQL and Python programming skills, including data querying, transformation, API integration, scripting, debugging, and automated testing.\nDemonstrated experience designing, developing, and maintaining enterprise data integrations, including RESTful APIs, data connectors, schema mappings, and secure data exchange between applications.\nHands-on experience integrating with at least one of the following platforms: Palantir, Databricks, or Elasticsearch, including working with platform APIs, data access mechanisms, or query interfaces.\nExperience working with structured, semi-structured, and unstructured enterprise data, including data modeling, schema management, data transformation, and retrieval optimization.\nExperience implementing secure, permission-aware data access, including authentication, authorization, identity propagation, sensitive-data handling, and source-level access restrictions.\nDemonstrated experience implementing data quality, validation, lineage, and traceability controls to ensure the accuracy, consistency, and reliability of enterprise data integrations.\nExperience developing data retrieval services or pipelines supporting analytics, intelligent search, AI applications, or retrieval-augmented generation (RAG) workflows.\nExperience troubleshooting complex data integration issues, including API failures, schema inconsistencies, query performance, authorization errors, and data quality problems.\nExperience with modern software engineering and delivery practices, including Git, code reviews, CI/CD pipelines, automated testing, and configuration management.\nAbility to translate technical and data governance requirements into secure integration designs, data contracts, test cases, and engineering documentation.\nStrong written and verbal communication skills, including the ability to collaborate with AI engineers, software developers, enterprise platform owners, and Government stakeholders.\nPreferred Qualifications\nHands-on integration experience with two or more of the following platforms: Palantir, Databricks, and Elasticsearch.\nExperience with Palantir data objects, relationships, APIs, or governed data-access capabilities.\nExperience with Databricks data products, SQL query services, data governance, lineage, or managed analytical datasets.\nExperience with Elasticsearch query APIs, index/alias management, document retrieval, and field-level access restrictions.\nExperience implementing RAG data pipelines, semantic or vector retrieval, document parsing, embeddings, and context preparation for LLM-powered applications.\nExperience supporting AI/ML or generative AI applications that require secure retrieval of enterprise data, source attribution, and permission-aware context assembly.\nExperience with cloud-native data engineering and containerized applications using AWS, Azure, Docker, Kubernetes, or comparable technologies.\nFamiliarity with Infrastructure as Code, DevSecOps practices, and automated deployment pipelines.\nExperience implementing controlled data synchronization, incremental updates, audit logging, and approved write-back operations across enterprise systems.\nExperience supporting Federal Government, Department of Defense, Intelligence Community, Department of Homeland Security, or similarly regulated data environments.\nFamiliarity with Government cybersecurity, privacy, data governance, access control, and software authorization requirements.\nExperience supporting technical demonstrations, Government acceptance testing, operational pilots, or production data integration sustainment.\nBenefits:\nExpression offers competitive salaries and benefits, such as:\n401k matching\nPPO and HDHP medical/dental/vision insurance\nEducation reimbursement up to $10,000/yr\nComplimentary life insurance\nGenerous PTO and 11 days of holiday leave\nCommuter Benefits Plan\nAbout Expression:\nFounded in 1997 and headquartered in Washington DC, Expression provides data fusion, data analytics, AI/ML, software engineering, information technology, and electromagnetic spectrum management solutions to the U.S. Department of Defense, Department of State, and national security community. Expression’s culture focuses on creating immediate and sustainable value for our clients via agile delivery of tailored solutions built through constant engagement with our clients. Expression was ranked #1 on the Washington Technology 2018's Fast 50 list of fastest-growing small business Government contractors and a Top 20 Big Data Solutions Provider by CIO Review.\nWe make sure to provide everyone with the tools and opportunities to grow while working on some of the newest technologies in the industry. We get excited about celebrating our professionals' milestones, accomplishments, promotions, overcoming challenges, and many other aspects that make an engaging collaborative environment.\nEqual Opportunity Employer/Veterans/Disabled\nExpression is an Equal Opportunity Employer. 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