Hatch IT
Data Engineer
Washington, DC · On-site · Full-time · Posted Aug 19, 2026
- Experience
- One of: bachelor’s degree plus 3 years of recent specialized experience; associate’s degree plus 7 years; major certification plus 7 years; or 11 years of recent specialized experience.
- Education
- Bachelor’s degree, associate’s degree, or major certification, with the stated experience alternatives; 11 years of recent specialized experience is also an alternative.
About the job
Designs and deploys secure, scalable data pipelines and machine-learning services that turn mission data into operational insights and decision support for a Department of Defense program.
What you'll do
- Build reusable data ingestion, transformation, preprocessing, and feature-engineering services for structured and unstructured data.
- Develop, deploy, and maintain machine-learning models and inference services in secure, containerized production environments.
- Collaborate with mission stakeholders and technical teams to analyze data, communicate findings, and integrate solutions into operational applications.
What they ask for
- Proficiency with Python, SQL, and distributed data frameworks, including Spark, Databricks, and PySpark.
- Experience developing machine-learning models from training through deployment using tools such as scikit-learn, TensorFlow, and XGBoost.
- Experience with data visualization and data storytelling using tools such as Palantir MSS Workshop and Slate applications.
- Secret clearance required; ability to obtain TS/SCI clearance.
Nice to have
- 4+ years in applied data science, Palantir Foundry development, or data-pipeline development.
- Familiarity with MLOps, API development, and secure cloud environments, including AWS, Azure, or Palantir Foundry.
Tools
Python, SQL, Spark, Databricks, PySpark, scikit-learn, TensorFlow, XGBoost
AI focus
Builds and deploys machine-learning and data-science capabilities, including classification, clustering, prediction, anomaly detection, pattern recognition, and decision support.
Model-written summary · the original posting is authoritative