Staff Data Engineer

LMI; Arlington (VA); On-site; USD 130,000 - 200,000; Full time

Job summary

LMI is seeking a Staff Data Engineer to build and sustain authoritative data products for Army logistics operations using Palantir Foundry. You will own scalable data pipelines, data models, and enterprise platforms to enable modernization and reliable insight.

Collaborate with engineers, designers, and stakeholders, ensuring data quality, security, and observability, while applying strong testing, CI/CD, and monitoring practices in a DoD setting.

Qualifications

• 8+ years of experience building production data systems.
• Strong proficiency with Python and SQL, plus modern data-engineering patterns.
• Experience designing data pipelines and products on Palantir Foundry or a comparable enterprise data platform.
• Experience with data modeling, ontology, data quality, and lineage.
• Strong software-engineering fundamentals including testing, source control, CI/CD, and monitoring.
• Experience supporting a Department of War customer.
• Active Secret clearance.

Responsibilities

• Own the architecture and implementation of scalable data pipelines and data products.
• Integrate and transform data from multiple Army and enterprise sources.
• Develop data models and ontology to support application modernization, reporting, and analysis.
• Design with data quality, lineage, security, observability, and long-term maintainability in mind.
• Establish engineering standards for testing, source control, deployment, and operations.
• Partner with software engineers, product designers, and customer stakeholders.
• Review technical designs, mentor engineers, and resolve complex data challenges.

Skills

Python

SQL

Data modeling

Ontologies

CI/CD

Education

Bachelor’s degree in CS/Engineering/IS/Data Science

Tools

Palantir Foundry

PySpark

CI/CD

Job description

LMI is seeking a Staff Data Engineer to build and sustain authoritative data products for Army logistics operations using Palantir Foundry.

Responsibilities

• Own the architecture and implementation of scalable data pipelines and data products.
• Integrate and transform data from multiple Army and enterprise sources.
• Develop data models and ontology to support application modernization, reporting, and analysis.
• Design with data quality, lineage, security, observability, and long-term maintainability in mind.
• Establish engineering standards for testing, source control, deployment, and operations.
• Partner with software engineers, product designers, and customer stakeholders.
• Review technical designs, mentor engineers, and resolve complex data challenges.

Requirements

• Bachelor’s degree in computer science, engineering, information systems, data science, or a related field, or equivalent practical experience.
• 8+ years of experience building production data systems.
• Strong proficiency with Python and SQL, plus modern data-engineering patterns.
• Experience designing data pipelines and products on Palantir Foundry or a comparable enterprise data platform.
• Experience with data modeling, ontology, data quality, and lineage.
• Strong software-engineering fundamentals including testing, source control, CI/CD, and monitoring.
• Experience supporting a Department of War customer.
• Active Secret clearance.

Technologies

• Python
• SQL
• Palantir Foundry
• CI/CD
• PySpark

Desired Qualifications

• Experience supporting the U.S. Army.
• Direct experience with Army Vantage.
• Experience with PySpark or other distributed data-processing technologies.
• Familiarity with Army ERPs and SAP-based systems.
• Experience with cloud platforms, DevSecOps, and infrastructure as code.
• Familiarity with API design and development, backend services, and service orchestration.

Location

• Arlington, VA (onsite)
• US-VA-Arlington

Salary

• USD 130,000 - 200,000 per year

Salary 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 location, internal equity, business considerations, client contract requirements, and candidate qualifications (education, experience, skills, and security clearances).