Palantir Data Engineer

JTEC Consulting is hiring a mid-level Palantir Data Engineer for an agile data team modernizing and operationalizing data workflows using Palantir Foundry. This 100% on-site role in Chantilly, VA supports end-to-end data delivery, from ingestion and transformation through mission-focused interfaces and ongoing O&M, with clear opportunities to collaborate across data engineering and analytics stakeholders.

What you’ll work on

• Architect, build, and optimize scalable ETL/ELT pipelines using Palantir Pipeline Builder and advanced Python.
• Manage end-to-end movement and ingestion of structured and unstructured data into local and enterprise-level storage repositories using compliant, approved methods.
• Create one-time extraction scripts and automated, recurring ingestion pipelines from heterogeneous data sources.
• Transform raw datasets into clean, well-governed enterprise and standalone data models ready for production analytics.
• Build direct integrations with external systems via RESTful APIs, parsing raw responses into clean, typed data objects.
• Design, build, and configure mission-focused user interfaces inside Palantir Workshop.
• Write, test, and deploy custom application functions using TypeScript to extend interface capabilities and user interactions.
• Develop custom tools, reusable code libraries, and micro-services to automate operational data engineering workflows.
• Act as a Tier 2 support escalation point to diagnose, triage, and remediate technical data issues reported by end-users.
• Translate customer feedback and operational pain points into detailed functional and technical requirements, including clear downstream impacts.
• Collaborate with Data Scientists, analysts, and stakeholders to define data schemas, exploration formats, and analytical transformation rules.
• Perform operations and maintenance (O&M), performance tuning, and feature enhancements on existing pipelines and codebases.
• Participate in peer code reviews, architectural brainstorming, and solution design sessions.
• Create and maintain comprehensive engineering documentation, including ETL field-level mappings, code location references, user guides, and access protocols.

What you’ll bring

• Current TS/SCI with agency-specific polygraph.
• U.S. citizenship.
• Bachelor’s degree in Computer Science, Information Systems, or a related technical discipline (or equivalent years of direct experience in lieu of a degree).
• 3+ years of related professional software engineering or data engineering experience.
• Strong written and verbal communication skills for collaboration in a cross-functional team.
• Hands-on proficiency with Palantir Foundry, including deep operational experience with Palantir Pipeline Builder and Palantir Workshop.
• Advanced proficiency in Python for data manipulation, ETL design, API parsing, and scripting.
• Professional experience writing and integrating TypeScript for front-end interfaces and custom functions.
• Experience connecting to external APIs, handling authentication, and serializing/parsing complex API payloads into relational or object-based data structures.
• Ability to process, clean, and model both structured and unstructured data, including edge cases and imperfect states.
• Capability to perform Tier 2 technical triage, assess architectural dependencies, and articulate technical trade-offs to non-technical stakeholders.

Tools you’ll use

Palantir Foundry, Palantir Pipeline Builder, Palantir Workshop, Python, TypeScript, RESTful APIs

Additional notes

• Location: 100% On-Site (Chantilly, VA)
• Relocation: Relo support for candidates outside the commuting area will be considered
• Salary: USD 140,000 - 160,000 per year

Preferred qualifications

• Experience working directly alongside Data Science teams to format and feature-engineer data for predictive modeling.
• Familiarity with software engineering best practices, including Git version control, continuous integration, and automated pipeline testing.
• Background in small-team, cross-functional environments emphasizing autonomy, rapid prototyping, and end-to-end ownership.
• Demonstrated success producing clear data lineage and technical documentation.