
Palantir Foundry Developer
3 weeks ago
Job Description: Palantir Foundry Developer
The Palantir Foundry role focuses on designing, developing, and maintaining data pipelines and applications and report building within the Palantir Foundry platform. The ideal candidate should have more than 8+ years of IT experience, with at least 2 years of specific experience working with Palantir and Python. The position emphasizes leveraging the Workshop application to build user interfaces, dashboards, and workflows that enable data-driven decision-making. This role requires technical expertise in Python, PySpark, and SQL, along with hands-on experience in Foundrys core components such as Code Repositories, Pipeline Builder, and Ontology. The candidate will collaborate with cross-functional teams, including data engineers, business users, and analysts, to deliver high-quality, actionable data solutions while ensuring performance and data integrity.
Responsibilities:
Develop and maintain data pipelines using Python, PySpark, and SQL for data transformations and workflows in Foundry.
Build user interfaces, dashboards, and visualizations within Foundrys Workshop application for data analysis and reporting.
Collaborate with stakeholders including data engineers, business analysts, and business users to gather requirements, design solutions, and ensure project success.
Ensure data quality and performance by implementing validation, testing, and monitoring processes.
Contribute to the Foundry ecosystem through code reviews, documentation, and sharing best practices to strengthen overall platform adoption and success.
Skills and Qualifications:
Bachelors degree in computer science, Data Science, or a related field; advanced degree preferred.
Palantir Foundry Expertise: Hands-on experience with Foundry components such as Workshop, Code Repositories, Pipeline Builder, and Ontology.
Programming Skills: Proficiency in Python and PySpark for data manipulation and pipeline development.
Database Knowledge: Strong SQL skills for data extraction, transformation, and query optimization.
Data Engineering Background: Experience with ETL/ELT workflows, data modeling, and validation techniques.
Cloud Platform Familiarity: Exposure to GCP, AWS or Azure is preferred.
Collaboration and Communication: Strong interpersonal and communication skills to work effectively with technical and non-technical stakeholders.
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