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Data Engineer (Vantage) - Clearance Required

Roles & Responsibilities

  • 5–8 years of experience in Data Engineering with expert proficiency in Python, SQL, and PySpark
  • Demonstrated experience with Army Vantage (Palantir Foundry) and the Advana ecosystem
  • Active DoD Secret Clearance required
  • Familiarity with Army data sources like IPPS-A, GCSS-Army, or GFEBS

Requirements:

  • Design, build, and maintain scalable ETL pipelines using Python and PySpark within Palantir Foundry
  • Develop and refine Objects (e.g., Soldiers, Equipment, Units) and their relationships to ensure a clean, accurate digital representation of Army operations
  • Assist with the cleanup of legacy data models and implement automated data quality checks
  • Build low-code/no-code applications and dashboards that allow senior leaders to access high-quality data in real-time

Job description

Overview:

LMI is seeking a Data Engineer to build the pipelines that power Army leadership decisions. You will transform raw data from authoritative Army sources into structured, actionable "Objects" within the Vantage (Palantir Foundry) environment.

 

Focus: Scaling data pipelines and ontology management within the Army Vantage/Advana ecosystem.

 

Active Secret clearance required.

 

Location: Hybrid; at least 3 days on client site in Crystal City VA or Aberdeen MD. Open to Remote. 

 

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 sectorsβ€”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:

Core Responsibilities:

  • Data Pipelines: Design, build, and maintain scalable ETL pipelines using Python and PySpark within Palantir Foundry.
  • Ontology Management: Develop and refine "Objects" (e.g., Soldiers, Equipment, Units) and their relationships to ensure a clean, accurate digital representation of Army operations.
  • Data Hygiene: Assist with the cleanup of legacy data models and implement automated data quality checks.
  • Decision Support: Build low-code/no-code applications and dashboards that allow senior leaders to access high-quality data in real-time.
  • Architecture: Implement Medallion Lakehouse concepts to organize data into Bronze, Silver, and Gold layers for downstream analytics.
Qualifications:

Qualifications:

  • Technical: 5–8 years of experience in Data Engineering with expert proficiency in Python, SQL, and PySpark.
  • Platform: Demonstrated experience with Army Vantage (Palantir Foundry) and the Advana ecosystem.
  • Clearing: Active DoD Secret Clearance required.
  • Bonus: Familiarity with Army data sources like IPPS-A, GCSS-Army, or GFEBS.

Travel: Minimal 10%

 

Location: Three days in Crystal City Va or Aberdeen MD. Open to Remote

 

Target salary range: $101,144 - $174,591

 

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.

 

#LI-SH1

 

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.

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