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Palantir Data Engineer

Job in McLean, Fairfax County, Virginia, USA
Listing for: Guidehouse
Full Time position
Listed on 2026-05-24
Job specializations:
  • IT/Tech
    Data Science Manager, Data Analyst
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

Job Family

Data Science Consulting

Travel Required

Up to 25%

Clearance Required

Ability to Obtain Public Trust

We are seeking a Palantir Data Engineer to design, build, and operate ontology-driven data products in Palantir Foundry (SaaS). This role emphasizes semantic data modeling, entity-centric design, and ontology-backed analytics and operational workflows, rather than pure pipeline engineering alone.

You will work closely with product owners, analysts, and mission stakeholders to translate real-world domains—such as case management, operations, and reporting—into well-governed ontologies composed of entities, relationships, properties, and actions. You will then implement and maintain the data pipelines and transformations that reliably populate and evolve those ontologies.

This role is ideal for an engineer who enjoys ontology-first thinking, data product design, strong governance, and enabling both analytics and operational use cases from a shared semantic foundation.

What You Will Do Ontology Design & Semantic Data Modeling (Primary Focus)
  • Design, implement, and maintain Palantir Foundry Ontologies
    , including entities, relationships, properties, actions, and permissions.
  • Translate business processes and domain requirements into clear, reusable entity and relationship models
    .
  • Ensure semantic consistency across datasets by enforcing standardized definitions, naming conventions, and relationship patterns.
  • Evolve ontologies over time while maintaining lineage, backward compatibility, and data contracts.
Build & Operate Foundry Pipelines Supporting the Ontology
  • Design and implement ingestion pipelines into Foundry from APIs, relational databases, object storage, file drops, and external partners.
  • Build transformation logic that materializes ontological entities and relationships from raw and curated data sources.
  • Implement incremental processing and CDC patterns to keep ontology-backed data current.
  • Optimize pipeline performance and reliability while maintaining clarity between raw, curated, and ontology-backed layers.
Deliver Ontology-Backed Analytics & Case Management Data Products
  • Produce analysis-ready datasets that power case views, entity timelines, dashboards, cohort analysis, and trend reporting.
  • Enable self-service analytics by ensuring ontology-backed datasets are intuitive, well-documented, and reusable.
  • Support both human workflows (case review, operations) and analytical/ML consumption from the same semantic foundation.
Governance, Lineage & Data Quality
  • Ensure datasets and entities are fully documented with ownership, descriptions, and business definitions.
  • Maintain end-to-end lineage from source systems through transformations into ontological entities.
  • Implement policy-based access controls and secure handling aligned to organizational and compliance requirements.
  • Operationalize data quality checks (freshness, completeness, validity) tied to mission-critical entities.
Reliability, Performance & Operational Excellence
  • Monitor pipelines and ontology-backed datasets using metrics, logs, and alerts.
  • Troubleshoot failures, conduct root-cause analysis, and implement preventive improvements.
  • Support environment promotion practices (DEV / TEST / PRE-PROD / PROD) with repeatable and auditable processes.
Cross-Team Collaboration
  • Partner with platform engineering, security, analytics, and application teams to align ontology design with operational needs.
  • Communicate complex ontology and data concepts clearly to both technical and non-technical stakeholders.
  • Participate in design and architecture reviews related to ontology evolution and data modeling standards.
What You Will Need
  • A Bachelor’s degree is required
  • A minimum of 3 years of experience building and operating production data pipelines and data models is required
  • Hands‑on experience with Palantir Foundry, or strong data engineering experience with the ability to ramp quickly.
  • Palantir Foundry Ontology experience, including:
  • Entity and relationship modeling
  • Ontology-backed actions and workflows
  • Permissioning and governance within the ontology
  • Strong proficiency in SQL and at least one data engineering language (Python preferred; Scala/Java acceptable).
  • Experience…
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