Palantir Foundry Engineer

Position: Palantir Foundry Engineer

Domain: Healthcare
Location: Nashville TN (Onsite from Day One)
Duration: 6 Months

Job Type Contract

Role Summary:

Seeking a hands-on Palantir Foundry Engineer to design ontology-driven data products build reliable data pipelines and operationalize them into secure reusable and observable assets supporting multiple healthcare applications (Workshop/Slate AIP/Actions). This role covers the full lifecycle-from raw data to governed versioned datasets powering enterprise analytics and AI workflows.

Key Responsibilities:

• Ontology & Data Modeling: Design and evolve Foundry Ontology objects schemas and data relationships with lineage tracking.
• Pipeline Engineering: Build and optimize Code Workbook transforms (SQL PySpark/Scala) implement incremental and snapshot pipelines and orchestrate DAGs.
• Data Operations: Configure schedules SLAs alerts and DQ checks; ensure idempotent and fault-tolerant execution.
• Governance & Security: Apply RBAC PII handling policy tags and least-privilege security principles.
• Performance Optimization: Tune joins caching and partitioning for cost and speed efficiency.
• DevOps & SDLC: Leverage Git CI/CD testing and versioning within Foundry.
• Application Integration: Expose ontology-backed data to apps (Workshop/Slate) APIs and AIP agents.
• Reliability: Manage incident response RCAs and create runbooks for data product stability.
• Documentation & Mentorship: Produce detailed documentation and enablement materials for engineering teams.

Required Qualifications:

• 7 years in Data Engineering/Analytics Engineering including 4 years hands-on Palantir Foundry.
• Strong command of Foundry Ontology Code Workbooks Pipelines and Permissions.
• Expertise in SQL PySpark/Scala and data pipeline optimization.
• Experience managing SLAs/SLOs alerts DQ frameworks and version control with Git/CI-CD.
• Familiar with AWS/Azure/GCP Parquet/Delta and cost/performance tuning.
• Understanding of data governance security and PII compliance.

Nice to Have:

• Experience building Workshop/Slate UIs AIP/Actions and Kafka/Kinesis streaming integrations.
• Exposure to observability tools (Datadog CloudWatch Prometheus) and FinOps practices.
• Established Foundry templates testing frameworks or data product catalogs.

Performance Metrics (First 90 180 Days):

• 99.5% pipeline success rate with SLAs and alerting in place.
• 20% reduction in runtime or compute cost.
• Zero P1 data incidents; 4h MTTR with automation.
• 3 reusable templates adopted by partner teams.
• Ontology versioning and lineage coverage for key healthcare domains.