Job Description
Responsibilities
- Design, develop, and maintain scalable data pipelines in Palantir Foundry using tools like Pipeline Builder, SQL, Python, and PySpark.
- Ingest, clean, transform, and curate data from diverse sources including enterprise systems, APIs, cloud platforms, and data warehouses.
- Build reliable datasets and reusable data products that support analytics, AI/ML, reporting, and operational workflows.
- Implement data quality controls, validation, lineage tracking, and monitoring to ensure trusted data consumption.
- Collaborate with cross-functional teams to translate business requirements into production-ready data solutions and model business entities.
- Optimize pipeline performance, troubleshoot production issues, and apply software engineering best practices such as version control and testing.
- Support data governance, compliance, ontology integration, and clear communication of technical insights to stakeholders.
What You Must Have
- At least a Bachelor's & Master's degree
- At least 4 years of experience
- Oral and written proficiency in English required
- Hands-on experience with Palantir Foundry data engineering
What Sets You Apart
- Experienced in building Ontology-ready data products in Palantir Foundry for operational applications, dashboards, workflows, AI/ML, and data science teams.
- Skilled with Palantir AIP, AI-enabled workflows, model development, feature engineering, and data products supporting GenAI use cases.
- Proficient in Palantir Application Development tools like Workshop, Quiver, Slate, Functions, Actions, and creating user-facing operational workflows.
- Knowledgeable in API integration, event-based ingestion, streaming data, SFTP, JDBC/ODBC connectivity, and automated data ingestion patterns.
-Familiar with CI/CD, automated testing, data observability, alerting, production support, incident management, and strong stakeholder communication and problem-solving skills.