Palantir Foundry

Technology->Data Engineering->Palantir Foundry

• Build, configure, and maintain data pipelines and workflows within Palantir Foundry to support business and analytics needs.
• Collaborate with stakeholders to gather requirements, translate them into Foundry-based solutions, and ensure alignment with expected outcomes.
• Perform data profiling, cleansing, and validation to improve data quality, consistency, and reliability across datasets.
• Develop and maintain reusable components, transformations, and data models to enable scalable analytics and reporting.
• Troubleshoot pipeline failures and performance bottlenecks; implement fixes and optimizations with clear documentation.
• Support deployments, versioning, and controlled releases of Foundry assets while following governance and best practices.
• Create clear technical documentation for pipelines, datasets, and operational procedures to support maintainability.
• Work effectively in a hybrid setup, ensuring consistent communication, timely updates, and smooth coordination across teams Minimum Qualifications:
• Education: BTECH, MCA, MSC, or MTECH.
• 3–5 years of overall experience in technology/data roles with hands-on delivery responsibilities.
• Minimum 3 years of experience working with Palantir and Palantir Foundry in building data solutions.
• Strong understanding of data pipeline concepts, data modeling, and data quality practices.
• Ability to analyze requirements, communicate effectively with stakeholders, and deliver within agreed timelines.
• Experience designing end-to-end Foundry solutions including dataset modeling, pipeline orchestration, and operational monitoring.
• Working knowledge of SQL and Python for data transformation, automation, and analytical workflows integrated with Foundry.
• Exposure to data governance practices such as access controls, lineage, and auditability in enterprise environments.
• Familiarity with CI/CD concepts and version control to support reliable releases and collaborative development.
• Strong problem-solving mindset with the ability to improve performance, reliability, and usability of data products.