LMI

Data Engineer (Vantage) - Clearance Required

Job Locations US-VA-Crystal City | US-MD-Belcamp
Posted Date 2 hours ago(5/14/2026 8:09 AM)
Job ID
2026-14057
# of Openings
1
Benefit Type
Salaried High Fringe/Full-Time

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

 

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

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

 

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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LMI is an Equal Opportunity Employer. LMI is committed to the fair treatment of all and to our policy of providing applicants and employees with equal employment opportunities. LMI recruits, hires, trains, and promotes people without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, pregnancy, disability, age, protected veteran status, citizenship status, genetic information, or any other characteristic protected by applicable federal, state, or local law. If you are a person with a disability needing assistance with the application process, please contact accommodations@lmi.org
Colorado Residents: In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.

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