Data Engineer, Mission Analytics & AI — Remote

Booz Allen Hamilton; Arlington (VA); On-site; USD 62,000 - 141,000; Full time

Job summary

Booz Allen Hamilton is seeking a Data Engineer (Mid) to build and maintain production data pipelines supporting DoW/DoD missions. You will work with mission experts, architects, data scientists, and cybersecurity professionals to transform diverse operational data into trusted, reusable assets.

Expect to code, integrate, deploy, monitor, and troubleshoot production systems, ensuring data is current, understandable, and appropriately protected for analytics and AI applications.

Qualifications

• 3+ years of experience with data engineering and production pipelines for DoW/DoD missions.
• Experience using Python and SQL to integrate data from enterprise databases, APIs, and operational systems.
• Experience building automated batch or streaming pipelines with data validation, failure recovery, and performance monitoring.
• Experience implementing cloud data infrastructure, including storage, data modeling, and query optimization.
• Secret clearance
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a technology field.

Responsibilities

• Build and maintain data pipelines across cloud and on-prem environments.
• Collaborate with mission experts, architects, data scientists, and cybersecurity professionals to turn data into trusted assets.
• Contribute to production systems through coding, integration, deployment, monitoring, and troubleshooting.
• Help analysts and AI applications access current, understandable, and protected data.

Skills

Python

SQL

Data pipelines

Cloud data infra

Secret clearance

Data engineering

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, or a technology field

Job description

Booz Allen Hamilton is seeking a Data Engineer (Mid) to build and maintain production data pipelines supporting DoW/DoD missions. You will work with mission experts, architects, data scientists, and cybersecurity professionals to transform diverse operational data into trusted, reusable assets.

Expect to code, integrate, deploy, monitor, and troubleshoot production systems, ensuring data is current, understandable, and appropriately protected for analytics and AI applications.