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Senior Data Engineer

Pay
Pay not listedSimilar roles state $127K–$190K
Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-Time
From the employer’s posting

Before you apply

Work authorization
Citizens onlySecret clearance required with eligibility for TS/SCI

What you’ll work on

Full posting
  • Build and maintain secure data connectors and APIs for Palantir, Databricks, and Elasticsearch

  • Design schema mappings and context preparation for RAG and AI document workflows

  • Implement permission-aware access controls and preserve data lineage and provenance

  • Build data validation and quality checks before records reach AI applications

  • Write automated tests and maintain interface documentation and runbooks

From the employer’s posting
Develop and integrate APIs, data connectors, and retrieval services for Palantir, Databricks, Elasticsearch, and other authorized enterprise data sources.
Design and maintain schema mappings, data transformations, and context-preparation processes to support retrieval-augmented generation (RAG)
Implement secure, permission-aware data access controls, including authentication, authorization, identity propagation, case-purpose restrictions, and source-level permissions.
Develop data validation, quality checks, and consistency controls to identify missing, stale, malformed, conflicting, or unauthorized records
Design and implement automated unit, integration, and regression tests for data connectors, APIs, schema mappings, data quality, and authorization boundaries.

What you’ll bring

All qualifications

Core experience

  • 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.

Preferred experience

  • 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.
Qualification wording
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 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.
Education & alternatives
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.

Benefits in the posting

Full benefits wording
  • 401k matching
  • PPO and HDHP medical/dental/vision insurance
  • Complimentary life insurance
  • Generous PTO and 11 days of holiday leave
  • Commuter Benefits Plan

From the employer’s posting.

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.

In the employer’s words · Read in context

Apply at Expression

Posting record

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 11, 2026today
Recorded sightings
1

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$127K–$190K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 2,229 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 6 and day 55.

From 12,958 similar postings that came down. Coming down is not always a hire.

Expression is hiring

4 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Its jobs tend to stay up a long time
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Azure
  • Databricks
  • Docker
  • Elasticsearch
  • Kubernetes
Where the posting names them
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.
- 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.
- 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 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.
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.
- 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.
- 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.
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.

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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 834, the most 1,323, and the latest week had 1,323.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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.

Source details

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Location & working pattern

Shirlington, VA

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Work authorization
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

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