Data Engineer with Palantir Foundry & AIP Exp
Role details
Job location
Tech stack
Requirements
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Palantir Foundry: Python Transforms, Pipeline Lineage, Schedules, Ontology Object design, Foundry Rules (Java), Media Sets.
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Palantir AIP: AIP Logic, AIP Automations, LLM integration basics, AIP Evals familiarity.
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Data Engineering: Data ingestion pipelines, schema management, Spark-based compute, incremental builds.
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Integration: Salesforce, Snowflake, REST APIs, CDO data connection patterns.
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Languages: Python (strong), Java (Foundry Rules), SQL (strong); C# or TypeScript a plus.
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DevOps: Docker, Git branching, CI/CD for Foundry repositories, code review workflows. Experience
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5-7 years of total experience in software engineering, data engineering, or platform development.
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2+ years of hands-on experience with Palantir Foundry in production environments, including pipeline ownership.
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Experience leading small engineering teams (3-6 people) in agile delivery environments.
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Proven ability to support and troubleshoot complex data platforms in a Day-2 support capacity.
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Experience with Salesforce or Snowflake integrations in enterprise settings preferred. Preferred Qualifications
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Experience with AI-powered document processing pipelines (OCR, PDF/Docx to Markdown, LLM-based extraction).
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Familiarity with Palantir AIP Evals, LLM-as-a-judge frameworks, and confidence scoring for AI outputs.
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Knowledge of Foundry Rules Java pipeline patterns, including .addObjectRid, .addLinkRid, and MaterializeOntologyObject patterns.
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Exposure to Campaign Lifecycle Management, lead management, or sales operations platforms.
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Understanding computing modules, OpenXML SDK, or other programmatic document generation approaches.