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). You'll 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.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 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.