PalantirBackendDataEngineer(Foundry)

Palantir Backend Data Engineer ( Foundry)

Position Summary

We are seeking an experienced Palantir Backend Data Engineer to design, develop, and optimize scalable data solutions on the Palantir Foundry platform. The ideal candidate should possess strong expertise in PySpark, Python, SQL, ETL development, and cloud-based data engineering. The role focuses on building robust pipelines, integrating enterprise data sources, and supporting advanced analytics and AI initiatives.

Experience

• 5+ years of experience in Data Engineering
• 2+ years of hands-on experience with Palantir Foundry
• Experience in BFSI, Insurance, or Financial Services is preferred

Key Responsibilities

Data Engineering & Pipeline Development

• Design, build, and maintain scalable data pipelines using PySpark and Palantir Foundry.
• Develop data ingestion frameworks for structured, semi-structured, and unstructured data sources.
• Build batch and incremental processing pipelines using Foundry Pipeline Builder and Code Repositories.
• Manage data lineage, metadata, and governance standards.

Data Integration & Transformation

• Integrate enterprise data from APIs, databases, cloud storage, and third-party systems into Foundry.
• Perform complex data transformations, cleansing, enrichment, and aggregation using PySpark.
• Develop reusable transformation frameworks and business rules.

Ontology & Data Modeling

• Design and maintain Ontology objects, relationships, actions, and business models.
• Translate business requirements into scalable semantic models.
• Support ontology-driven applications and analytics.

Performance & Optimization

• Optimize Spark jobs for performance, scalability, and cost efficiency.
• Implement data quality checks, monitoring, and automated validation frameworks.
• Troubleshoot production pipelines and resolve performance bottlenecks.

Collaboration & Governance

• Partner with Data Scientists, Architects, Product Owners, and Business stakeholders.
• Support data governance, security, compliance, and auditability requirements.
• Maintain technical documentation and operational runbooks.

Required Technical Skills

Must Have

• PySpark, Spark SQL, Python
• Advanced SQL
• Palantir Foundry

o Pipeline Builder

o Code Repository

o Data Connections

o Ontology Manager

o Data Lineage

• ETL/ELT Design & Development
• Data Modeling and Data Warehousing Concepts
• Git-based version control

Good to Have

• Azure / AWS / GCP
• Databricks
• Airflow
• REST API Integration
• Delta Lake / Snowflake
• Palantir Certifications (Data Engineer, Application Developer, AI Engineer)