Data Engineer

General Dynamics Information Technology • San Diego, WA

3d • $83,927 - $113,549 • Onsite

About The Position

The Data Engineer builds and sustains the data foundation for the POTFF Enterprise Data and Analytics function. The role acquires, integrates, and prepares data from the Government-designated Human Performance System of Record (such as HPDMS) and other Government-approved sources; develops scalable, reproducible pipelines and curated, analysis-ready datasets on the Government-furnished technology stack; and maintains data quality, lineage, and governance controls. The engineer provides expertise to the enterprise data science team and directly supports Data Scientists, Senior Data Scientists, and the Data Science Advisor.

The position supports customer activities at various CONUS sites. It is onsite, with 40 scheduled hours per week and less than 10% travel required. The posting is contingent and expected to start in 2026.

Requirements

• At least three years of professional experience in data engineering, database development, or data pipeline development; at least five years if qualifying without a bachelor’s degree.
• Bachelor’s degree in a quantitative or computing discipline, with documented coursework or professional application in programming, databases, and quantitative analysis; candidates without the degree may qualify through the stated experience alternative.
• Demonstrated proficiency in SQL and Python or a comparable language used for data engineering.
• Experience building and operating data pipelines, including ETL/ELT design, data modeling, data quality checks, reproducible pipeline design, and Git version control.
• Ability to communicate clearly with analysts and non-technical stakeholders and document technical work for continuity.
• U.S. citizenship required.
• Must currently possess Secret clearance and be able to obtain Top Secret/SCI, as stated in the requisition; the posting also says Secret or Top Secret clearance, or ability to obtain clearance.

Nice To Haves

• Experience with Palantir Foundry, including ontology development, or a comparable data-integration platform.
• Experience with distributed processing frameworks such as Databricks and Apache Spark (PySpark).
• Familiarity with Power BI semantic modeling and Microsoft Power Platform, including Power Apps and Power Automate.
• Experience deploying analytics or machine-learning models into applications and familiarity with MLOps concepts.
• Experience working in a DoW-authorized cloud environment.
• Experience with human performance, health, clinical, or biomedical data.

Responsibilities

• Design, implement, and maintain scalable ETL/ELT pipelines on the Government-furnished technology stack for batch and scheduled processing and data transformation.
• Fuse structured, semi-structured, and unstructured data from across the POTFF enterprise—including HPDMS, assessment and wearable data, and other Government-approved systems—into curated, analysis-ready datasets.
• Implement data quality controls, validation rules, lineage documentation, and performance tuning; monitor scheduled and orchestrated workloads and resolve failures.
• Develop and maintain data models, data dictionaries, metadata, and transformation logic under version control, and document data sources, assumptions, and processing steps.
• Prepare and curate text and other unstructured data for NLP and LLM use cases performed by the data science team in Government-approved tools.
• Support integration of curated data products into Government-furnished visualization and low-code tools and deployment of analytic products into operational workflows, including basic MLOps practices when directed.
• Apply Government data governance, security, and privacy requirements, including DoW Impact Level 5, HIPAA, and Privacy Act protocols, and implement data access controls as directed.
• Collaborate with Government personnel, clinicians, program staff, and the data science team to identify data sources, improve data quality in Government systems, and translate analytical requirements into data requirements.
• Provide data engineering expertise and technical guidance to Data Scientists and Senior Data Scientists.

Benefits

• 401(k) with company match.
• Medical, dental, and vision plan options, including health plans with Health Savings Accounts.
• Paid education and certifications, and professional growth opportunities.
• Paid vacation and holidays; the broader rewards description also lists sick, personal, parental, military, bereavement, and jury duty leave.
• Paid Family Leave of up to 160 hours in a rolling 12-month period for eligible employees.
• Short- and long-term disability benefits and life, accidental death and dismemberment, personal accident, critical illness, and business travel and accident insurance offerings.
• Full flex work weeks where possible.
• Internal mobility support and access to cutting-edge technology.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level