Design, build, and maintain robust data pipelines to ensure reliable data flow across the enterprise.
Maintain data pipeline schedules, orchestrate workflows, and monitor the overall health of data pipelines to ensure continuous data availability.
Create, update, and optimize data connections, datasets, and transformations to align with business needs.
Troubleshoot and resolve data sync issues, ensuring consistent and correct data flow from source systems.
Collaborate with cross-functional teams to uphold data quality standards and ensure accurate data is available for use.
Utilize Palantir Foundry to establish data connections to source applications, extract and load data, and design complex logical data models that meet functional and technical specifications.
Develop and manage data cleansing, consolidation, and integration mechanisms to support big data analytics at scale.
Build visualizations using Palantir Foundry tools and assist business users with testing, troubleshooting, and documentation creation, including data maintenance guides.

Bachelor’s Degree and minimum 2 years of prior relevant experience.
Graduate Degree and a minimum of 0 to 2 years of prior related experience.
In lieu of a degree, minimum of 6 years of prior related experience.
2+ years experience with designing and developing data pipelines in PySpark, Spark SQL, SQL or Code Build.
2+ years experience in building and deploying data synchronization schedules and maintaining data pipelines using Palantir Foundry.
2+ years of experience with Data Pipeline development or ETL tools such as Palantir Foundry, Azure Data Factory, SSIS, or Python.
2+ years of experience in Data Integration.

Senior Associate, Data Engineer

Key skills