Description

You will design and operationalize ontology-first data products in Palantir Foundry, owning the full lifecycle from raw sources to governed, versioned datasets.

Responsibilities

• Model Object Types, relationships, and semantics while enforcing schema evolution and defining authoritative datasets with lineage.
• Build Code Workbook transforms using SQL, PySpark, or Scala, orchestrating multi-stage DAGs with incremental patterns and backfills.
• Configure schedules, SLAs/SLOs, alerts, and data quality tests to ensure high reliability and idempotency.
• Apply RBAC, object-level permissions, and policy tags for governance, integrating with enterprise identity systems.
• Optimize performance through join/partition tuning, caching strategies, and shuffle minimization while monitoring runtime metrics.

Required Skills

• 7+ years in data engineering with 4+ years hands-on Palantir Foundry experience at scale.
• Deep expertise in Foundry Ontology, Code Workbooks, Pipelines, Materializations, and object permissions.
• Strong SQL and PySpark/Scala proficiency, including UDFs, window functions, and partitioning/bucketing strategies.
• Proven operational excellence with SLAs/SLOs, alerting, data quality frameworks, and rollback procedures.
• Fluency with Git, CI/CD for Foundry code repos, and test automation for transforms.
• Hands-on experience with cloud storage and compute (AWS/Azure/GCP) and file formats like Parquet/Delta.
• Strong grasp of data governance including PII handling, masking, and security models within Foundry.

Preferred Skills

• Building Workshop/Slate UX tied to ontology objects or authoring Actions for AIP integration.
• Experience with streaming ingestion patterns (e.g., Kafka/Kinesis) and observability stacks like Datadog.

Key Skills

Education

Any Graduate