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Palantir Data Engineer

JTEC Consulting Chantilly, VA

Chantilly, VA

Today

$140k - $160k/yr Full time Backend Developer API APIs

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Job Description

JTEC Consulting is seeking a mid-level Palantir Data Engineer to support an agile data team modernizing and operationalizing data workflows using Palantir Foundry. The role is based in Chantilly, VA and focuses on building production-ready pipelines, integrating external systems, extending Palantir interfaces with TypeScript, and providing Tier 2 support for technical data issues.

Onsite Location

Chantilly, VA (100% onsite)
Relocation: relocation support for candidates outside the commuting area will be considered

Salary

USD 140,000 - 160,000 per year

Experience and Education

Minimum experience: 3+ years
Education: Bachelor’s degree in Computer Science, Information Systems, or a related technical discipline (or equivalent years of direct experience considered in lieu of a degree)

Key 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-level 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 raw 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.
Serve as a Tier 2 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 downstream impacts on the existing 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 for 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.

Required Qualifications

Security clearance: current TS/SCI with agency-specific polygraph
Citizenship: U.S. citizenship
3+ years of related professional software engineering or data engineering experience
Effective written and verbal communication skills for cross-functional collaboration
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, including authentication and serialization/parsing of complex API payloads into relational or object-based data structures
Strong capability processing, cleaning, and modeling both structured and unstructured data from 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

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
Experience in cross-functional, small-team settings emphasizing autonomy, rapid prototyping, and end-to-end ownership
Demonstrated success producing clear data lineage and technical documentation

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