Data Engineer – Army Vantage / Palantir Foundry - Clearance Required

Overview

LMI is seeking an experienced Data Engineer - Army Vantage / Palantir Foundry to support the U.S. Army Training Information System (ATIS) program. This hands-on role will develop, maintain, and improve ATIS data products and integrations, with a primary focus on capabilities delivered through Army Vantage and Palantir Foundry.

The Data Engineer will transform authoritative ATIS data into reliable, reusable enterprise data products and ensure Vantage/Foundry capabilities integrate effectively with the broader ATIS data ecosystem. The ideal candidate has hands-on Foundry experience, strong data-engineering skills, and the ability to independently identify and resolve end-to-end data quality and integration issues across ATIS and Vantage/Foundry.

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.

Responsibilities

• Develop, maintain, troubleshoot, and enhance ATIS data products, datasets, pipelines, applications, dashboards, and related capabilities within Army Vantage/Palantir Foundry.
• Design, build, and sustain production-quality data pipelines and transformations using Python, SQL, PySpark, and native Foundry capabilities.
• Develop and maintain Foundry ontology objects, relationships, and data models that make authoritative ATIS data understandable, reusable, and accessible to approved users.
• Integrate authoritative ATIS data with Vantage/Foundry and other Army enterprise data sources while maintaining data quality, lineage, and appropriate access controls.
• Trace, diagnose, and drive resolution of end-to-end data quality and integration issues across ATIS source data, interfaces, transformations, pipelines, and Vantage/Foundry products.
• Develop Foundry-native dashboards, applications, reports, and other data products to support Army analytics, visualization, reporting, and mission needs.
• Implement data-quality validation, monitoring, scheduling, error handling, and other practices necessary to operate reliable production data products.
• Apply sound software and data-engineering practices, including version control, peer review, testing, documentation, and CI/CD where supported.
• Work directly with product owners, engineers, architects, analysts, and users to translate mission needs into practical technical solutions and support appropriate use of authoritative ATIS data.
• Document solutions, share knowledge, and build team capability so ATIS can sustain and extend its data and Foundry capabilities without creating single-person dependencies.
• Operate as a self-directed member of the Agile team, taking ownership of technical outcomes and independently driving problems toward resolution.

Qualifications

Required Qualifications

• Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, or a related technical field, or equivalent relevant experience.
• 4+ years of professional experience in data engineering, data integration, software development, or development of production data products.
• Hands-on experience developing or maintaining solutions in Palantir Foundry and/or Army Vantage, with sufficient familiarity to contribute with limited platform-specific ramp-up.
• Strong proficiency in SQL and Python for data transformation, analysis, automation, and troubleshooting.
• Experience designing, building, and maintaining ETL/ELT pipelines involving complex or disparate datasets.
• Experience with data modeling, including schemas, keys, relationships, reference data, and transformation of source data into reusable data products.
• Experience with Foundry ontology, semantic data models, or comparable enterprise data structures.
• Experience with PySpark, Spark, Pandas, or comparable technologies for transforming complex datasets.
• Demonstrated ability to troubleshoot data pipelines, integrations, data-quality issues, and production data products, including tracing problems across source systems and downstream consumers.
• Ability to work independently from mission intent or a desired end state while collaborating effectively with multidisciplinary technical and product teams.
• Strong analytical, problem-solving, communication, and documentation skills, including the ability to explain technical concepts to nontechnical stakeholders.
• Active DoD Secret security clearance.

Preferred Qualifications

• Direct experience developing and sustaining data products within Army Vantage.
• Experience integrating DoD/Army authoritative data sources and working with enterprise data-quality, lineage, governance, and access-control requirements.
• Experience developing Foundry-native applications, dashboards, reports, or custom interfaces.
• Experience applying software-engineering practices such as Git/version control, peer review, automated testing, and CI/CD to data products.
• Familiarity with APIs, cloud data services, and enterprise system integration.
• Experience working within an Agile or SAFe Agile Release Train (ART) environment.
• Applicable DoD 8140 cybersecurity/workforce qualification, where required.
• Experience supporting Army, DoD, federal, or other secure/regulated mission systems.

Target salary range: $120,000 - $155,000

Disclaimer:

The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances.

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