Data Engineer - Clearance Required

Logistics Management Institute

5d•Hybrid

About The Position

LMI seeks an experienced Data Engineer to support the U.S. Army’s Holistic Health & Fitness (H2F) initiative as a member of the Analytics functional team within the H2F Program Support Team. The Data Engineer is responsible for designing, building, and maintaining data pipelines and data services that enable scientific analysis, analytics, and user engagement activities within the Holistic Health and Fitness Management System (H2FMS). This role focuses on data ingestion, transformation, storage, and accessibility, ensuring that data supporting research, analytics, and decision support is reliable, well-structured, and available for authorized use. The Data Engineer works closely with the Technical Project Manager, data governance specialists, epidemiologists, research psychologists, tactical sports scientists, data scientists, and software teams to translate analytic and research requirements into scalable data solutions under Government direction. This role does not set independent data policy or analytic strategy. 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.

Requirements

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
Demonstrated experience building and maintaining data pipelines and data integration solutions.
Familiarity with data transformation, storage, and analytics enablement concepts.
Experience working with structured and semi-structured data.
Ability to collaborate effectively within multidisciplinary teams spanning analytics, research, and software.
Strong problem-solving and communication skills.
Ability to obtain and maintain a Secret security clearance.

Nice To Haves

Experience supporting analytics or research-driven data environments.
Familiarity with cloud-based data services or analytics platforms.
Experience preparing data for dashboards, reporting, or AI/ML workflows.
Prior experience supporting DoW or federal customers.

Responsibilities

Design, develop, and maintain data ingestion and transformation pipelines supporting H2FMS analytics and research use cases.
Integrate data from multiple sources, including surveys, wearable and performance data, health and injury datasets, and operational systems as directed.
Ensure pipelines are reliable, scalable, and support downstream analytic and reporting needs.
Support development of analytic data models optimized for reporting, dashboards, and advanced analytics.
Work with data governance staff to ensure data models align with approved data definitions and standards.
Assist with management of structured and semi-structured data stores used within H2FMS.
Enable data access and preparation for data scientists and AI/ML engineers, ensuring data is usable for modeling and analysis.
Support feature preparation and data validation activities under Government and senior analytic direction.
Assist in troubleshooting data-related issues impacting analytics or models.
Support monitoring and resolution of data quality issues, including completeness, consistency, and timeliness.
Implement basic validation, logging, and error-handling mechanisms within data pipelines.
Coordinate with data governance and analytics teams to address recurring data issues.
Collaborate with epidemiologists, research psychologists, and tactical sports scientists to understand analytic data needs.
Coordinate with software teams to support integration between data services and application components.
Support documentation and communication of data pipeline designs and dependencies.