Palantir Foundry Engineer

Position: Palantir Foundry Engineer

Location: Nashville TN

Duration: 6 Months

Role Summary:

Hands-on Foundry specialist who can design ontology-first data products engineer high-reliability pipelines and operationalize them into secure observable and reusable building blocks used by multiple applications (Workshop/Slate AIP/Actions). Youll own the full lifecycle: from raw sources to governed versioned materialized datasets wired into operational apps and AIP agents.

Core Responsibilities:

• Ontology & Data Product Design: Model Object Types relationships and semantics; enforce schema evolution strategies; define authoritative datasets with lineage and provenance.
• Pipelines & Materializations: Build Code Workbook transforms (SQL PySpark/Scala) orchestrate multi-stage DAGs tune cluster/runtime parameters and implement incremental snapshot patterns with backfills and recovery.
• Operationalization: Configure schedules SLAs/SLOs alerts/health checks and data quality tests (constraints anomaly/volume checks); implement idempotency checkpointing and graceful retries.
• Governance & Security: Apply RBAC object-level permissions policy tags/PII handling and least-privilege patterns; integrate with enterprise identity; document data contracts.
• Performance Engineering: Optimize joins/partitions caching/materialization strategies file layout (e.g. Parquet/Delta) and shuffle minimization; instrument with runtime metrics and cost controls.
• Dev Productivity & SDLC: Use Git-backed code repos branching/versioning code reviews unit/integration tests for transforms; templatize patterns for reuse across domains.
• Applications & Interfaces: Expose ontology-backed data to Workshop/Slate apps wire Actions and AIP agents to governed datasets; publish clean APIs/feeds for downstream systems.
• Reliability & Incident Response: Own on-call for data products run RCAs create runbooks and drive preventive engineering.
• Documentation & Enablement: Produce playbooks data product specs and runbooks; mentor engineers and analysts on Foundry best practices.

Required Qualifications:

• 7 years in data engineering/analytics engineering with 4 years hands-on Palantir Foundry at scale.
• Deep expertise in Foundry Ontology Code Workbooks Pipelines Materializations Lineage/Provenance and object permissions.
• Strong SQL and PySpark/Scala in Foundry; comfort with UDFs window functions and partitioning/bucketing strategies.
• Proven operational excellence: SLAs/SLOs alerting data quality frameworks backfills rollbacks blue/green or canary data releases.
• Fluency with Git CI/CD for Foundry code repos test automation for transforms and environment promotion.
• Hands-on with cloud storage & compute (AWS/Azure/GCP) file formats (Parquet/Delta) and cost/perf tuning.
• Strong grasp of data governance (PII masking policy tags) and security models within Foundry.

Nice to Have:

• Building Workshop/Slate UX tied to ontology objects; authoring Actions and integrating AIP use cases.
• Streaming/event ingestion patterns (e.g. Kafka/Kinesis) materialized into curated datasets.
• Observability stacks (e.g. Datadog/CloudWatch/Prometheus) for pipeline telemetry; FinOps/cost governance.
• Experience establishing platform standards: templates code style testing frameworks domain data product catalogs.

Success Metrics (90 180 Days):

• 99.5% pipeline success rate with documented SLOs and active alerting.
• < 20% runtime/cost reduction via optimization and materialization strategy.
• Zero P1 data incidents and 4h MTTR with playbooks and automated remediation.
• 3 reusable templates (ingestion CDC enrichment) adopted by partner teams.
• Ontology coverage for priority domains with versioned contracts and lineage.

Example Work Youll Own:

• Stand up incremental CDC pipelines with watermarking & late-arrivals handling; backfill historical data safely.
• Define business-ready ontology for a domain and wire it to Workshop apps and AIP agents that trigger Actions.
• Implement DQ gates (null/dup checks distribution drift) that fail fast and auto-open incidents with context.
• Build promotion workflows (dev staging prod) with automated tests on transforms and compatibility checks for ontology changes.