Palantir Data Engineer

Overview

A Palantir Data Engineer designs, builds and maintains complex, scalable data pipelines within the Palantir Foundry platform. Key responsibilities include; integration, processing, managing large datasets using PySpark/Python and SQL, creating data models and collaborating with cross-functional teams to drive AI enabled production ready analytics.

• Pipeline Development:
  Build, maintain and optimize robust data pipelines and workflows in Palantir Foundry using Python, PySpark and SQL.
• Data Modeling & Quality:
  Develop ontologies, map datasets to objects, and ensure high data quality, lineage, and security.
• System Optimization:
  Monitor and tune performance for large-scale data processing.
• Platform Maintenance:
  Ensure Foundry platform uptime, managing data ingestion and integration.

• 2-3 years’ in data engineering, ETL workflows and big data tech (i.e. Spark, Kafka, AWS).
• Strong proficiency with Python, PySpak, SQL and data modelling.
• Palantir expertise should include certification in Palantir Foundy (Code Repos, Workbook, Pipeline Builder).
• Experience with in Agile environments and ability to work with large, complex datasets.
• Common technology tools include; JIRA, Git, Confluence.
• Platform Tools include;
  Palantir, Docker/Kubernetes, AWS (S3, Glue).

Thank you for your interest in this opportunity. If you are selected to move forward in the process, we will contact you directly. If you do not hear from us, we encourage you to continue visiting our website for other roles that may be a good fit.

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