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Palantir Foundry Engineer

Abode Tech Zone

Position Title


Palantir Foundry Engineer


Domain EXP


(Healthcare Domain)


Location


Nashville TN (Onsite Day one)


Duration


6 Month


Rate


Open



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Job Description



Role Summary


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



Core Responsibilities

  • Ontology & Data Product Design: Model Object Types, relationships, and semantics ; enforce schema evolution strategies; define uthoritative 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 , lerts/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 ctions and IP 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 ctions and integrating IP 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)
  • &Client;99.5% pipeline success rate, with documented SLOs and active lerting .
  • <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 You'll 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 IP agents that trigger ctions .
  • 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.
Vacancy posted 1 day ago
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