Palantir Platform Engineer
Listed on 2026-09-06
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IT/Tech
Data Engineering, Data Analyst
Palantir Platform Engineer
Herndon, VA (fully on-site, no remote option)
** Please do NOT apply if you do not have an active Poly clearance. Those without a Poly will not be considered.**
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 Dev Ops 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.
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
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 Dev Ops methodologies
- Experience leveraging AI to augment data pipelines
- Strong skills in Validation of data products
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