Lead Data Architect

Responsibilities

• Design, build, and maintain end-to-end ETL/ELT pipelines using PySpark, Spark SQL, and Python
• Architect scalable data frameworks to support high-performance analytics and operational workflows
• Configure and manage data connections, Pipeline Builder, and Contour for data exploration
• Develop and maintain ontology objects to ensure semantic consistency across applications
• Collaborate with domain experts to model data into ontology-driven applications like Workshop and Quiver
• Manage code repositories and version control within Foundry to promote maintainable engineering practices

Requirements

• 8+ years of experience in data engineering or related roles
• Deep hands-on experience with Palantir Foundry (Data Connections, Pipeline Builder, Contour, Code Repositories, Ontology Management, Workshop, and Quiver)
• Strong proficiency in PySpark, Spark SQL, and Python
• 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

Preferred Qualifications

• Experience with cloud platforms such as 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

Benefits

• Paid time off including vacation, company holidays, personal days, and sick leave
• Medical, dental, and vision coverage
• Retirement savings plans (e.g., 401(k))
• Life and disability insurance
• Employee assistance programs

About the Company

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world. With a team of 340,000 members in more than 50 countries, we deliver end-to-end services leveraging strengths in AI, cloud, and data to address the entire breadth of our clients' business needs.