Data Engineer - Clearance Required

Overview

LMI is seeking a skilled Data Engineer to join our team and contribute to developing innovative software programs that support activities for the Army’s AI2C organization, located in Pittsburgh, PA.

Responsibilities

• Lead data engineering efforts within Palantir Foundry (Vantage), including ontology design, pipeline development, and data integration for Army AI2C mission applications
• Build, maintain, and optimize Foundry pipelines using Python-based transforms (PySpark/Pipeline Builder), Code Repositories, and Foundry’s data connection framework
• Develop and maintain data engineering workflows in Databricks, including notebooks, Delta Lake tables, and Spark jobs, for workloads that complement or feed into the Foundry environment
• Write, design, and implement efficient, reusable, and reliable code using Python, PySpark, SQL, and TypeScript/JavaScript as needed for Foundry Workshop or Slate applications
• Translate complex data science and analytics outputs into governed, reusable data products surfaced through Foundry and Databricks
• Champion AI-forward, platform-first development practices and guide the team in implementing AI/ML features and data-driven experiences
• Engage with Army managers and representatives in a consultative capacity to identify data platform needs, explore innovative data-driven solutions including AI applications, and build strategic relationships that expand our development footprint
• Collaborate effectively with data scientists, UX designers, and software developers using Git, participating in code reviews and adopting Agile methodologies

Qualifications

• Minimum Qualifications: Bachelor’s degree in Computer Science, Data Science, Data Engineering, Software Engineering, Information Systems, or a related field, or equivalent work experience
• 3-5 years of experience in data engineering, with hands-on experience building and operating applications on the Palantir Foundry (Vantage) platform
• Demonstrated experience with Foundry pipeline development (PySpark/Pipeline Builder), Code Repositories, ontology/object modeling, and Foundry Workshop application building
• Working experience with Databricks, including notebooks, Delta Lake, and Spark-based data processing, as a secondary platform to Foundry
• Proficiency in Python and SQL for data manipulation and pipeline development (pandas, PySpark, numpy, or similar)
• Familiarity with data visualization approaches (D3.js, Plotly, Recharts, or Foundry-native Workshop widgets) for surfacing pipeline outputs
• Demonstrated experience in planning, analyzing, designing, implementing, testing, and maintaining data pipelines and applications for an enterprise-level system
• Familiarity with Git, Agile methodologies, CI/CD, and automated deployments
• Demonstrated experience in leadership roles, technical mentorship, or client relationship management
• Active Secret Clearance or ability to obtain one is required

Additional Preferred Qualifications

• Experience integrating AI/ML capabilities into Foundry or Databricks-based applications and identifying strategic AI use cases
• Familiarity with AI frameworks and APIs (OpenAI, Anthropic Claude, LangChain, or similar) and with Foundry AIP
• Knowledge of statistical analysis and machine learning concepts
• Experience with Storybook for component development, documentation, and design system management
• Hands-on deployment experience across multiple environments and platforms, including classified/air-gapped Foundry instances
• Knowledge of the Army software development process and its technologies or experience developing applications for classified data
• Proven track record of expanding technical scope or footprint with government customers

On-Site (Pittsburgh) Candidates Preferred

Target Salary Range

The target salary range for this position is $101,144 - $174,591. 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.