JTEC Consulting is seeking a mid-level Palantir Data Engineer to join an agile data team modernizing and operationalizing data workflows using Palantir Foundry. This role is focused on building production-ready data pipelines, integrating external systems, supporting mission-focused user experiences, and providing Tier 2 technical triage while contributing to ongoing operations and maintenance.
Role Responsibilities
- 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 storage repositories using compliant, approved methods.
- Create one-time extraction scripts and automated recurring ingestion pipelines from heterogeneous data sources.
- Transform raw, disparate datasets into clean, well-governed enterprise and standalone data models suitable for production analytics.
- Build direct integrations with external systems via RESTful APIs, parsing responses into clean, typed data objects.
- Design, build, and configure mission-focused user interfaces within 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 escalation point to diagnose, triage, and remediate technical data issues reported by end-users.
- Convert customer feedback and operational pain points into detailed functional and technical requirements, including clear downstream impacts to the environment.
- Collaborate with Data Scientists, analysts, and project stakeholders to define data schemas, exploration formats, and analytical transformation rules.
- Perform operations and maintenance (O&M), performance tuning, and feature enhancements on existing data pipelines and codebases.
- Participate in peer code reviews, architectural brainstorming, and solution design sessions.
- Create and maintain engineering documentation, including ETL field-level mappings, code location references, user guides, and access protocols.
Required Qualifications
- 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
- Effective written and verbal communication skills for a collaborative, cross-functional team
- Hands-on proficiency with Palantir Foundry, including deep operational experience with Palantir Pipeline Builder and Palantir Workshop
- Advanced proficiency in Python (data manipulation, ETL design, API parsing, 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
- Strong experience processing, cleaning, and modeling both structured and unstructured data, including edge cases and imperfect states
- Ability to perform Tier 2 technical triage, assess architectural dependencies, and communicate technical trade-offs to non-technical stakeholders
Technologies
- Palantir Foundry
- Palantir Pipeline Builder
- Palantir Workshop
- Python
- TypeScript
- RESTful APIs
Security Clearance Requirement
- Current TS/SCI with polygraph
Location, Work Style, and Relocation
- Chantilly, VA (100% onsite)
- Relocation support for candidates outside the commuting area will be considered
Salary
USD 140,000 - 160,000 per year.
Preferred Qualifications
- Experience working directly with 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 cross-functional, small-team environments emphasizing autonomy, rapid prototyping, and end-to-end ownership
- Demonstrated success producing clear data lineage and technical documentation