Palantir Platform Engineer TS/SCI (FSP)

Description As a Palantir Platform Engineer, you will play a pivotal role in integrating custom ETL workflows within the Palantir ecosystem. Your responsibilities will include connecting ETL conditioners to Palantir tooling, which enhances observability and accelerates data conditioning efforts. You will ensure that stakeholders maintain comprehensive insight into each phase of the transformation process, leveraging your expertise in data ontology, logging, and monitoring. Utilizing your skills in PySpark and Python, you will design and implement robust data pipelines that support seamless data flow and transformation.

In this position, you will also harness AI to augment and optimize data pipelines, driving greater speed and efficiency in processing large datasets. Your focus on data governance and validation will be essential as you prepare products for integration into advanced analytics tools, ensuring data quality and reliability. Experience with DevOps practices will be valuable as you manage deployment and operational aspects of the platform, while your familiarity with Palantir Foundry and ontology modeling will help you navigate complex data environments. Success in this role will be supported by a strong background in building scalable ETL solutions, implementing monitoring frameworks, and collaborating with cross-functional teams to deliver actionable data insights.

* This role requires an active TS/SCI FSP to start *

Requirements Desired Skills:

• Experience with Palantir Foundry
• Strong understanding of Ontology and Data Ontology
• Expertise in building and integrating ETL Pipelines
• Proficiency in PySpark and Python
• Experience with Logging and Monitoring solutions
• Knowledge of Data Governance best practices
• Familiarity with DevOps methodologies
• Experience leveraging AI to augment data pipelines
• Strong skills in Validation of data products

Preferred Skills/Experience

• Experience connecting ETL conditioners to Palantir tooling
• Background in increasing observability and accelerating data conditioning
• Experience ensuring end-to-end insight into data transformation processes
• Familiarity with integrating validated products into analytics tools for data exploitation