Lead Data Architect (Palantir Lead Architect)

Capgemini•Chicago, IL

7d•Onsite

About The Position

We are seeking a highly experienced Palantir Foundry Lead Data Engineer to architect, develop, and optimize scalable data solutions using Palantir Foundry. This senior role is ideal for a data engineering expert who thrives in complex, ontology-aware environments and can lead the design of robust data pipelines and applications that drive actionable insights. You will play a pivotal role in shaping our data strategy, collaborating with stakeholders across the organization, and ensuring the integrity, performance, and cost-efficiency of our data ecosystem. While familiarity with Generative AI (GenAI) is a plus, your core expertise should lie in data architecture, pipeline development, and Foundry platform mastery.

Requirements

8+ years of experience in data engineering or related roles.
Strong proficiency in PySpark, Spark SQL, and Python.
Deep hands-on experience with Palantir Foundry, including: Data Connections, Pipeline Builder, Contour, Code Repositories, Ontology Management, Workshop and Quiver.
Solid understanding of data modeling, data governance, and access control.
Proven ability to troubleshoot complex data issues and optimize performance.
Excellent communication and collaboration skills.

Nice To Haves

Experience with cloud platforms (e.g., Azure).
Familiarity with Snowflake and its integration with Foundry.
Exposure to Generative AI (GenAI) and its application in data workflows.
Knowledge of data security, compliance, and metadata management.

Responsibilities

Design, build, and maintain end-to-end ETL/ELT pipelines using PySpark, Spark SQL, and Python.
Architect scalable data frameworks that support high-performance analytics and operational workflows.
Conduct data cleansing, transformation, and validation to ensure data quality and consistency.
Configure and manage data connections, Pipeline Builder, and Contour for data exploration and visualization.
Develop and maintain ontology objects, ensuring semantic consistency and reusability across applications.
Manage code repositories and version control within Foundry, promoting modular and maintainable engineering practices.
Collaborate with data owners and domain experts to ingest, transform, and model data into ontology-driven applications such as Workshop and Quiver.
Maintain clarity on the end-to-end architecture and data flow, ensuring seamless integration from ingestion to ontology.