Palantir Developer

Palantir Developer - Foundry, Ontology, PySpark Location: Remote Contract: 6-months initial Rate: $100 - $125 per hour We’re seeking a Palantir Developer to help build and enhance data products in Foundry, including PySpark-based transforms, ontology development, and Workshop applications. The role requires strong hands-on experience with Foundry deployments using Pipeline Builder/Code Repo, working with existing ontologies, and delivering interactive experiences in Workshop using Vega-Lite and TypeScript. Responsibilities • Develop PySpark transforms in Palantir Foundry using Pipeline Builder / Code Repo workflows. • Build, extend, and maintain ontology objects by working with and adapting existing ontologies (not just greenfield). • Develop Workshop applications including: • Vega-Lite visualizations • TypeScript UI/app logic and integrations • Apply best practices for continuous Foundry deployment, supporting reliable release and iteration cycles. • Collaborate with data/platform teams to translate business/data requirements into Foundry pipelines, schemas, and ontology structures. • Work effectively with Palantir AIP and related platform conventions. Required Qualifications • 2+ years of continuous Foundry deployment experience. • Strong hands-on experience with: • Pipeline Builder / Code Repo • PySpark transforms • Solid experience building Workshop applications using: • Vega-Lite • TypeScript (excellent hands-on proficiency) • Proven experience working with existing ontologies (extensions/updates/migrations) rather than only building new ones. • Demonstrated experience developing and delivering in Foundry end-to-end (deployment through operational use). • Experience with Palantir AIP. Preferred Qualifications (Nice to Have) • Experience with ontology modeling patterns, ontology governance, and schema evolution. • Familiarity with Foundry operational tooling and troubleshooting (pipeline performance, debugging, validation). • Experience integrating Workshop with ontology entities/attributes and existing data products. Success Measures • PySpark transforms are production-ready, well-tested, and reliably deployed via continuous delivery processes. • Ontology changes are consistent, maintainable, and compatible with downstream consumers. • Workshop apps deliver clear, performant visualization and UI experiences using Vega-Lite + TypeScript. • Changes integrate cleanly with existing ontologies and AIP-aligned practices.