Data Engineer Internship Jobs in Chester, VA (NOW HIRING)

LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.

Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors, helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.

**This role is onsite at Fort Lee (VA)

LMI is seeking an Associate Data Engineer to support the U.S. Army Combined Arms Support Command at Fort Lee, Virginia. You will help build and maintain the data pipelines and trusted data products used to support the Army Quartermaster Corp, sustainment, and operational decision-making.

This is a hands-on role for an early-career engineer with a solid foundation in Python, SQL, and data integration.

• Build, test, and maintain data pipelines.
• Collect, transform, and integrate data from databases, files, APIs, and enterprise systems.
• Develop Python and SQL code used in data-processing and integration workflows.
• Perform data profiling, validation, and quality checks.
• Help document data sources, transformations, lineage, and technical processes.
• Investigate pipeline failures and data-quality issues.
• Support the development of trusted data products for reporting, analysis, and Army decision-making.
• Use source control, automated testing, and established engineering practices.
• Work with Army stakeholders to understand data requirements.
• Participate in code reviews and contribute to reusable engineering patterns.

Minimum Qualifications:

• Bachelor's degree in computer science, data science, engineering, information systems, mathematics, or a related field, or equivalent practical experience.
• One or more years of relevant data, software, or analytics engineering experience. Relevant internships, military experience, and substantial academic projects may be considered.
• Working knowledge of Python and SQL.
• Understanding of relational databases, data structures, and data-transformation concepts.
• Experience building or supporting ETL or ELT workflows.
• Familiarity with Git or another source-control system.
• Ability to communicate technical issues clearly and work effectively within a multidisciplinary team.
• The ability to obtain and maintain a DoD Secret clearance is required. Please note, only US Citizens can obtain a clearance.
• Ability to work onsite at Fort Lee, Virginia.

Preferred Qualifications:

• Active DoD Secret clearance.
• Experience supporting the U.S. Army or another Department of Defense organization.
• Familiarity with Army logistics, sustainment, readiness, supply chain, or maintenance data.
• Experience with Palantir Foundry, Databricks, or another enterprise data platform.
• Experience with cloud data services in AWS or Azure.
• Familiarity with data-quality, lineage, orchestration, or monitoring tools.
• Experience using automated testing or continuous-integration practices.
• Relevant technical certification or military occupational experience.

Applicants must meet eligibility requirements for a U.S. Government security clearance. Only US Citizens are eligible for a security clearance. For this position, LMI will only consider applicants with security clearances or applicants who are eligible for security clearances, due to the nature of the work.

Applicants must meet eligibility requirements for a U.S. Government security clearance. Only US Citizens are eligible for a security clearance. For this position, LMI will only consider applicants with security clearances or applicants who are eligible for security clearances, due to the nature of the work.