Data Engineer - Agile Defense

About Agile Defense

At Agile Defense we know that action defines the outcome and new challenges require new solutions. That’s why we always look to the future and embrace change with an unmovable spirit and the courage to build for what comes next.

Our vision is to bring adaptive innovation to support our nation's most important missions through the seamless integration of advanced technologies, elite minds, and unparalleled agility—leveraging a foundation of speed, flexibility, and ingenuity to strengthen and protect our nation’s vital interests.

Requisition #: 1653

Job Title: Data Engineer

Location: Camp Smith, HI

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.

Location: In Person: Honolulu (Camp H.M. Smith), HI

Key Objectives:

Objective 1: Design and Maintain Scalable Data Science Services

• Plan, develop, and maintain reusable services for data ingestion, transformation, and feature engineering that support AI/ML workflows.
• Implement core data science capabilities, such as entity resolution, classification, clustering, or prediction, within containerized environments that adhere to CI/CD, version control, and testing standards.
• Collaborate with DevSecOps engineers to integrate services into secure production environments using tools like Databricks, Docker, and Terraform.
• Ensure services meet performance, reliability, and security requirements consistent with DoD enterprise and cloud-native architecture.

Objective 2: Build and Operationalize AI/ML Solutions

• Develop and deploy standalone or embedded ML models for tasks such as decision support, automation, anomaly detection, and pattern recognition.<