Data Engineer - SPACECOM

Requisition #: 1758

Job Title: Data Engineer - SPACECOM

Location: On-Site, Colorado Springs, CO

Clearance Level: Top Secret, Must Have Clearance to Start

Job Description

Agile Defense is seeking a Data Scientist / Engineer to support the design, development, and operational deployment of scalable, AI-enabled data solutions within the Department of Defense’s CDAO ADA IR program. This role is part of a multidisciplinary team integrating advanced analytics, machine learning, and engineering practices into mission-critical environments at Combatant Commands.

You will help shape and deploy data pipelines, pre-processing workflows, feature engineering strategies, and machine learning services within secure, containerized environments. The ideal candidate brings a hybrid of statistical modeling fluency and hands-on software engineering expertise. You will collaborate closely with product managers, full-stack developers, platform engineers, and mission stakeholders to transform raw data into meaningful insights and decision-support tools.

This role requires strong technical communication skills, a collaborative mindset, and experience working in agile environments that value reproducibility, testing, and continuous delivery. Familiarity with cloud-based data platforms such as Databricks, Palantir, or AWS-native data services is highly preferred.

Education and Background

Typically has a Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field (masters degree preferred)., and 3+ years of experience in data engineering or software engineering, with demonstrated experience in designing and managing complex data pipelines., or equivalent relevant work experience; e.g., each year of work experience may be substituted for each year of education required.

Years of Experience

3+ years

Required Skills

• Experience with data visualization and storytelling using tools such as Palantir's MSS Workshop and Slate applications

Preferred Skills

• 4+ years of experience in applied data science, Palantir Foundry development, or data pipeline development.
• Proficient in Python, SQL, and distributed data frameworks (e.g., Spark, Databricks, PySpark).
• Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost).
• Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure, Palantir Foundry).
• Strong understanding of data validation, model testing, and performance evaluation techniques.
• Excellent technical communication skills, with the ability to explain complex concepts to non-technical audiences.

Working Conditions

Must be able to work onsite at a SCIF