Data Engineer | VA Claims Modernization

LMI is seeking a talented and mission-driven Data Engineer to support the U.S. Department of Veterans Affairs (VA), with a focus on modernizing Veterans Benefits Administration (VBA) claims processing. This role will help transform how critical claims information is collected, integrated, processed, and delivered, enabling faster, more accurate, and more efficient services for Veterans and their families.

In this hands-on engineering role, you will design, build, and optimize scalable data pipelines and modern data solutions that support VA disability compensation claims, evidence management, workflow automation, and operational analytics. You will work with complex datasets spanning claims submissions, military service records, medical evidence, examination information, and claims processing activities, transforming disparate information into secure, reliable, and actionable data products.

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.

• Data Pipeline Engineering: Design, develop, and maintain scalable, secure ETL/ELT pipelines using Python, SQL, PySpark, and modern data engineering frameworks to support VA claims processing, data integration, and analytics.

• VA Claims Data Integration: Integrate structured, semi-structured, and unstructured data from authorized VA systems, claims applications, evidence repositories, medical records, external data sources, and enterprise databases. Develop reusable integrations using REST APIs, JSON, and secure data exchange methods.

• Claims Processing Modernization: Engineer data solutions that streamline claims intake, evidence collection, validation, workflow routing, status tracking, and downstream processing. Help reduce manual reconciliation, eliminate redundant data movement, and improve access to accurate claims information.

• Cloud Data Engineering: Develop and optimize solutions using approved AWS, Azure, or comparable cloud environments, leveraging cloud-native data processing, storage, orchestration, and analytics services.

• Data Architecture & Modeling: Design and maintain relational, dimensional, and analytical data models supporting claims operations, reporting, and enterprise data products. Apply modern data lake, data warehouse, and lakehouse architecture patterns to improve scalability, accessibility, and performance.

• Big Data Processing: Use distributed processing technologies such as Apache Spark and PySpark to transform and process large-scale datasets. Optimize SQL queries, database performance, transformations, and data-processing workflows for reliability and efficiency.

• Data Quality & Governance: Establish automated data validation, reconciliation, monitoring, and quality controls to improve accuracy, completeness, consistency, and timeliness. Maintain metadata, data lineage, traceability, and documented business rules across critical claims datasets.

• Workflow Automation & Orchestration: Build repeatable batch, incremental, and event-driven data workflows using modern orchestration tools. Implement automated…