Data Engineer

General Dynamics Information Technology (GDIT) is hiring a Data Engineer to build and sustain the data foundation for the POTFF Enterprise Data and Analytics function. The role integrates and prepares Government-approved data, maintains scalable pipelines and curated datasets, and enforces data quality, lineage, governance, security, and privacy controls in support of the data science team.

Responsibilities

• Design, implement, and maintain scalable extract-transform-load and extract-load-transform (ETL/ELT) pipelines on the Government-furnished technology stack (e.g., SQL Server, Databricks, and Apache Spark (PySpark)) for batch and scheduled processing and data transformation
• Fuse disparate structured, semi-structured, and unstructured data sources from across the POTFF enterprise, including the Government-designated Human Performance System of Record (e.g., HPDMS), assessment and wearable data, and other Government-approved systems, into curated, analysis-ready datasets
• Implement rigorous data quality controls, validation rules, lineage documentation, and performance tuning to ensure reliable, reproducible, and secure pipelines; 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 to ensure transparency and operational continuity
• Prepare and curate text and other unstructured data to support Natural Language Processing (NLP) and Large Language Model (LLM) use cases executed by the data science team within Government-approved tools
• Support the integration of curated data products into Government-furnished visualization and low-code tools and the deployment of analytic products into operational workflows, including basic machine-learning operations (MLOps) practices where directed by the Government
• Apply Government data governance, security, and privacy requirements, including DoW Impact Level 5 (IL5), HIPAA, and Privacy Act protocols, to all data handling, and implement data access controls as directed by the Government
• Collaborate with Government personnel, clinicians, program staff, and the data science team to identify new data sources, improve the quality of data entered into Government systems, and translate analytical requirements into data requirements
• Provide data engineering expertise and technical guidance to Data Scientists and Senior Data Scientists

Preferred

• 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 with the Microsoft Power Platform (Power Apps and Power Automate)
• with deploying analytics or machine-learning models into applications and with MLOps concepts
• Experience working in a DoW-authorized cloud environment
• Experience with human performance, health, clinical, or biomedical data
• Palantir Foundry
• Ontology Development
• Data Integration Platforms
• Distributed Processing
• Databricks
• Apache Spark
• PySpark
• Power BI Semantic Modeling
• Microsoft Power Platform
• Power Apps
• Power Automate
• Analytics Model Deployment
• Machine Learning Model Deployment
• MLOps
• DoW-Authorized Cloud Environments
• Human Performance Data
• Health Data
• Clinical Data
• Biomedical Data

Benefits

• 401K with company match
• Comprehensive health and wellness packages
• Internal mobility team dedicated to helping you own your career
• Professional growth opportunities including paid education and certifications
• Cutting-edge technology you can learn from
• Paid vacation and holidays
• Medical plan options, some with Health Savings Accounts
• Dental plan options
• A vision plan
• A 401(k) plan offering the ability to contribute both pre- and post-tax dollars up to the IRS annual limits and receive a company match
• Full flex work weeks where possible
• A variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave
• Typically, 15 days of paid leave per calendar year for vacations, personal business, and illness; prorated based on the employee’s date of hire
• An additional 10 paid holidays per year; prorated based on the employee’s date of hire
• Up to 160 hours of paid leave in a rolling 12-month period through the GDIT Paid Family Leave program for eligible employees
• Short- and long-term disability benefits
• Life, accidental death and dismemberment, personal accident, critical illness, and business travel and accident insurance are provided or available

Company

• Technology and mission services for U.S. government, defense, intelligence.
• Falls Church, Virginia, USA
• https://www.gdit.com/
• Founded in 1999
• 10001+ employees

Qualifications

• Top Secret
• 3 + years of related experience
• Yes
• Bachelor's degree in a quantitative or computing discipline, including but not limited to computer science, computer engineering, software engineering, information systems, data science, data engineering, mathematics, statistics, or geospatial science or geoinformatics, with documented coursework or professional application in programming, databases, and quantitative analysis. A candidate without the degree qualifies with the experience stated under Required Minimum Experience/Skills
• Minimum of three (3) years of professional experience in data engineering, database development, or data pipeline development. Without the bachelor's degree, a minimum of five (5) years of such experience
• Demonstrated proficiency in SQL and in Python or a comparable language used for data engineering, demonstrated through professional work experience
• Demonstrated experience building and operating data pipelines, including ETL/ELT design, data modeling, data quality checks, reproducible pipeline design, and version control (Git)
• Ability to communicate clearly with analysts and non-technical stakeholders and to document technical work for continuity
• 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 with the Microsoft Power Platform (Power Apps and Power Automate)
• With deploying analytics or machine-learning models into applications and with MLOps concepts
• Experience working in a DoW-authorized cloud environment
• Experience with human performance, health, clinical, or biomedical data
• Minimum of three (3) years of professional experience in data engineering, database development, or data pipeline development. Without the bachelor’s degree, a minimum of five (5) years of such experience.

Required skills

• Apache Spark (PySpark), Data Engineering, Data Modeling, Data Pipeline Development, Data Quality, Databricks, ETL/ELT, Git, MLOps, Palantir Foundry, Power BI Semantic Modeling, Python, SQL

Preferred skills

• Experience working in a DoW-authorized cloud environment

Experience

• 3+ years