Data Engineer
persistent
Job Description
- Build and maintain end-to-end data pipelines in Palantir Foundry using Pipelines, Transforms, and Code Repositories.
- Develop robust data transformations using Python / PySpark to support large-scale processing use cases.
- Perform complex data preparation and transformations using SQL (joins, aggregations, validations).
- Work on Ontology / Object Modeling in Foundry to enable reusable, business-friendly data assets.
- Implement data quality checks, monitoring, and reconciliation to ensure trusted datasets.
- Support data migration / modernization initiatives, ensuring performance, scalability, and reliability.
- Collaborate with stakeholders (Data Engineers, Analysts, Architects, Product teams) to deliver high-quality data products.
- Troubleshoot pipeline failures, performance bottlenecks, and optimize compute/storage usage.
- Ensure adherence to data governance, security, and best practices (as applicable to the platform/program).
Expertise You'll Bring:
- Strong problem-solving and debugging skills across data pipelines and transformations.
- Ability to work independently in a fast-paced environment and collaborate across teams.
- Clear communication skills for stakeholder updates and requirement understanding.
- Delivery ownership mindset with attention to data accuracy, performance, and reliability.
- Experience with Databricks (PySpark, Spark SQL, Delta Lake).
- Familiarity with Airflow or other workflow orchestration tools.
- Understanding of data governance, cataloguing, and security concepts.
- Domain experience in Airlines / Travel / Enterprise data platforms.