Palantir Foundry Engineer

The Palantir Foundry Engineer is responsible for building and maintaining Foundry code repositories, transforms, and datasets.

This role involves designing scalable data ingestion pipelines, implementing batch and streaming workflows, ensuring data quality, and optimizing performance.

The engineer will collaborate with cross-functional teams to translate business requirements into Foundry data models and applications while adhering to security and governance standards.

Key Responsibilities Build and maintain Foundry code repositories, transforms, and datasets.

Design and implement scalable data ingestion pipelines and batch/stream workflows.

Create and maintain schema definitions, data lineage, and provenance.

Implement data quality checks, monitoring, and alerting for production pipelines.

Configure and enforce dataset access controls and security policies within Foundry.

Optimize performance of transforms (Spark/Python/SQL) and dataset materialization.

Collaborate with cross-functional teams to translate business requirements into Foundry data models and applications.

Document patterns, best practices, and contribute to internal Foundry governance.

Required Qualifications BS/MS in Computer Science, Engineering, or related field, or equivalent experience.

Excellent communication and collaboration skills.

3+ years of experience in data engineering; 1+ year in Palantir Foundry strongly preferred.

Strong proficiency in Python, Spark (PySpark), and/or SQL.

Experience with data modeling, ETL/ELT patterns, data lineage, and versioning.

Practical knowledge of Foundry concepts: Datasets, Transforms, Code Repositories, and basic exposure to Ontologies.

Familiarity with DevOps practices, CI/CD, and Git-style workflows.

Strong troubleshooting and performance tuning skills.

Preferred Qualifications 2+ years of production Foundry experience (designing transforms, ontology usage).

Experience with cloud platforms (AWS, GCP, Azure).

Familiarity with containerization, orchestration (Kubernetes), and infrastructure as code.

Experience with data governance, cataloging, and policy enforcement.

Exposure to streaming frameworks (Kafka, Kinesis) and real-time transforms.

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