Jobs in the United States

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Added 26 mins ago
KC
Electrical Engineering Supervisor
King County
Seattle, WA
- $77.35 to $93.51 USD / hour
…zero-emissions fleet, your leadership will help shape innovative, sustainable mobility in our region. If you are passionate about empowering others, fostering collaboration, and driving…
Added 2 hours ago
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Principal Engineer, Cloud Software
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United States
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Chicago, IL
…thought possible. That foundation is now the essential AI trust infrastructure for the Fortune 1000. We’re hiring mission-driven talent to put those leaders at the center of our…
Added 2 hours ago
E
Senior Data Engineer
Expression
Shirlington, VA
- $180,000 to $200,000 USD / year
The 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…
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United States
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Technical Support Engineer
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NH
Empower Global Infrastructure as our Next Technical Support Engineer (B2W)!
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- $102,300 to $209,500 USD / year
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Austin, TX · Seattle, WA · Herndon, VA
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AP
Director, Forward Deployed Security Architecture
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Gaithersburg, MD
- $169,320 to $222,232.5 USD / year
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Director, Forward Deployed Security Architecture
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Gaithersburg, MD · Gaithersburg
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Expression

Senior Data Engineer

Shirlington, VA, United States

$180,000 to $200,000 USD / year

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Job details

Pay: $180,000 to $200,000 USD / year
Posting language: English
Posted: Nov 11, 2026

Original job 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). This 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. The 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. This 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. Security Clearance: Secret clearance required with eligibility for TS/SCI. Location: Shirlington, VA

Key Responsibilities

Design, develop, and maintain secure enterprise data integrations connecting 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 supporting 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 to support retrieval-augmented generation (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 throughout data retrieval and AI processing workflows.
Develop data validation, quality checks, and consistency controls to identify missing, stale, malformed, conflicting, or unauthorized records before they are consumed by downstream AI applications.
Optimize data retrieval and API performance, including 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 generated outputs can be traced to supporting source records and comply with established access controls.
Design and implement automated unit, integration, and regression tests for data connectors, APIs, schema mappings, data quality, and authorization boundaries.
Implement secure error handling, audit logging, and observability to monitor data integration 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.
Collaborate 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 enterprise data schemas, interfaces, or access requirements evolve.
Participate in technical design reviews, code reviews, engineering planning, and cross-functional troubleshooting activities.
Support technical demonstrations, prototype evaluations, Government acceptance testing, and operational pilot deployments.

Required 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 of hands-on experience developing enterprise data pipelines, APIs, or governed data services.
Strong SQL and Python programming skills, including data querying, transformation, API integration, scripting, debugging, and automated testing.
Demonstrated experience designing, developing, and maintaining enterprise data integrations, including RESTful APIs, data connectors, schema mappings, and secure data exchange between applications.
Hands-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.
Experience working with structured, semi-structured, and unstructured enterprise data, including data modeling, schema management, data transformation, and retrieval optimization.
Experience implementing secure, permission-aware data access, including authentication, authorization, identity propagation, sensitive-data handling, and source-level access restrictions.
Demonstrated experience implementing data quality, validation, lineage, and traceability controls to ensure the accuracy, consistency, and reliability of enterprise data integrations.
Experience developing data retrieval services or pipelines supporting analytics, intelligent search, AI applications, or retrieval-augmented generation (RAG) workflows.
Experience troubleshooting complex data integration issues, including API failures, schema inconsistencies, query performance, authorization errors, and data quality problems.
Experience with modern software engineering and delivery practices, including Git, code reviews, CI/CD pipelines, 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, including the ability to collaborate with AI engineers, software developers, enterprise platform owners, and Government stakeholders.

Preferred Qualifications

Hands-on integration experience with two or more of the following platforms: 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 that require 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.

Benefits:

Expression offers competitive salaries and benefits, such as:

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

About Expression:

Founded 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. We 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. Equal Opportunity Employer/Veterans/Disabled Expression is an Equal Opportunity Employer. If you require a reasonable accommodation during the application or interview process, please submit your request to our Human Resources department through the application portal.

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Jobs in the United States