About this Job :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.
Location :Dallas TX, New York, New Jersey, Atlanta GA, Chicago IL
Your Role :• 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.
Ontology-Aware Application Development
• 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.
Required Qualifications• 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.
Preferred Qualifications• 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.
The base compensation range for this role in the posted location is: 160,000- 220,000
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
- Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
- Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
- Life and disability insurance
- Employee assistance programs
- Other benefits as provided by local policy and eligibility
