Intrepid, an SPA Company, brings more than 20 years of experience supporting the Department of Defense and U.S. Government, consistently setting the standard for excellence in the federal marketplace. Committed to advancing the mission of the U.S. Warfighter, Intrepid leverages technological superiority to deliver innovative solutions across air, space, land, and sea domains. We are proud to foster a collaborative, dynamic work environment, offering competitive compensation and an industry-leading 401k contribution. Our team is built through merit and achievement, and we’re always looking for the best and brightest to join us in our growth. We treat our people like family, we are mission-focused, and we give back! Join us today.

Our Financial Management & Business Analysis Portfolio supports the U.S. Army Space and Missile Defense Command (USASMDC); the Office of the Assistant Secretary of the Army (ASA) Financial Management and Comptroller (FM&C); the U.S. Army Financial Management Command (USAFMCOM); the Defense Health Agency (DHA); and many other DoD customers.  We ensure the Army FM systems and processes are modernized and integrated to provide a complete range of financial and cost information needed for the Army to conduct business transactions, provide accountability to the public, and to support performance reporting and decision making.  We provide effective functional systems support, user technical support, training support, and governance support of the Army's modernized and deployed FM domain ERP systems (GFEBS / GFEBS-SA / GCSS-A (Finance)), ensuring technological capabilities maturation and evolution aligns with Army and FM domain goals and objectives. 

We are looking for a Data Engineer to join our team to support the Defense Health Agency Chief Data and Analytics Office in building an enterprise data orchestration layer for the Military Health System. The team will be bringing together information from diverse defense and federal systems to build scalable data pipelines, APIs, and data products that improve how critical health data is integrated, accessed, and used

• Design, develop, and maintain scalable, production-ready data pipelines using Spark, Python, and SQL in a Databricks environment.
• Integrate and transform diverse health, financial, and operational datasets into reliable, reusable data products.
• Develop data models and analytics datasets that support enterprise reporting and operational decision-making.
• Build and maintain API-based integrations for ingesting and exchanging data across systems.
• Monitor, troubleshoot, and optimize scheduled workflows and production pipelines for performance, reliability, and scalability.
• Implement data validation, quality checks, lineage, and governance practices that improve trust in data products.
• Contribute to automated testing, code reviews, technical documentation, and reusable engineering patterns.
• Collaborate with engineers, architects, analysts, and customer stakeholders to translate data needs into practical technical solutions.

Required Qualifications:

• Possess an active Secret clearance
• Bachelor's degree in Computer Science, Information Systems, Software Engineering, or a related field 
• 3 to 10 years of data engineering, software engineering, or related technical experience
• Strong proficiency with Python and SQL

• Experience with Apache Spark or similar distributed data-processing frameworks
• Experience working with Databricks or a similar modern data platform
• Experience building and maintaining production data pipelines and ETL/ELT processes
• Working knowledge of data modeling and transforming raw data into reusable analytics datasets or data products
• Experience integrating or consuming data through REST APIs
• Experience troubleshooting and optimizing data pipelines for performance and reliability
• Familiarity with data validation, quality, governance, security, privacy, and compliance considerations
• Experience with Git-based development workflows and modern software engineering practices
• Comfort working in terminal and command-line environments
• Experience using AI-assisted development tools to accelerate routine engineering tasks, testing, documentation, and debugging
• Strong communication skills and experience working with customers or stakeholders to understand and resolve data needs
• Ability to navigate ambiguity, learn unfamiliarsystems, and independently drive assigned work toward resolution

Desired Qualifications: 

• AWS cloud experience
• Experience working with very large datasets, including datasets containing billions of records
• Experience with Palantir Foundry
• Experience with Advana or similar DoW data environments
• Experience with GitLab, CI/CD pipelines, or automated deployment workflows
• Experience working with federal health, financial, or other regulated and sensitive data

Required Qualifications:

• Possess an active Secret clearance
• Bachelor's degree in Computer Science, Information Systems, Software Engineering, or a related field 
• 3 to 10 years of data engineering, software engineering, or related technical experience
• Strong proficiency with Python and SQL

• Experience with Apache Spark or similar distributed data-processing frameworks
• Experience working with Databricks or a similar modern data platform
• Experience building and maintaining production data pipelines and ETL/ELT processes
• Working knowledge of data modeling and transforming raw data into reusable analytics datasets or data products
• Experience integrating or consuming data through REST APIs
• Experience troubleshooting and optimizing data pipelines for performance and reliability
• Familiarity with data validation, quality, governance, security, privacy, and compliance considerations
• Experience with Git-based development workflows and modern software engineering practices
• Comfort working in terminal and command-line environments
• Experience using AI-assisted development tools to accelerate routine engineering tasks, testing, documentation, and debugging
• Strong communication skills and experience working with customers or stakeholders to understand and resolve data needs
• Ability to navigate ambiguity, learn unfamiliarsystems, and independently drive assigned work toward resolution

Desired Qualifications: 

• AWS cloud experience
• Experience working with very large datasets, including datasets containing billions of records
• Experience with Palantir Foundry
• Experience with Advana or similar DoW data environments
• Experience with GitLab, CI/CD pipelines, or automated deployment workflows
• Experience working with federal health, financial, or other regulated and sensitive data