Palantir Platform Engineer – AI-Driven ETL Pipelines

B4Corp; Herndon (VA); On-site; USD 144,000 - 240,000; Full time

Benefits offered by this job

401k with employer match

Phantom stock

Medical insurance (UHC)

Dental coverage

Vision coverage

PTO seven weeks per year

Referral bonus

Job summary

B4Corp is seeking a Palantir Platform Engineer in Herndon, VA, to integrate ETL workflows within the Palantir ecosystem and enhance data conditioning and observability. The candidate will work with PySpark and Python to build scalable data pipelines while ensuring data quality and governance across all transformation stages.

Responsibilities include leveraging AI to optimize pipelines, coordinating with DevOps for platform deployment, and integrating validated products into analytics tools for

Qualifications

• Experience with Palantir Foundry and ontology modelling is required.
• Strong ability to design and implement robust ETL pipelines.
• Proficiency with PySpark and Python for large-scale data processing.
• Experience with logging, monitoring, and data governance best practices.
• Familiarity with DevOps practices and deploying data platforms.
• Ability to leverage AI to optimize data pipelines and improve performance.

Responsibilities

• Integrate custom ETL workflows within the Palantir ecosystem and connect ETL conditioners to Palantir tooling to improve observability.
• Design and implement scalable data pipelines for large datasets.
• Ensure data quality, governance, and validation across transformations.
• Collaborate with cross-functional teams to deliver actionable data insights and support advanced analytics tools.

Skills

Palantir Foundry

Ontology

ETL pipelines

PySpark

Python

Logging & Monitoring

Data governance

DevOps

AI in data pipelines

Data validation

Tools

Palantir tooling

Job description

B4Corp is seeking a Palantir Platform Engineer in Herndon, VA, to integrate ETL workflows within the Palantir ecosystem and enhance data conditioning and observability. The candidate will work with PySpark and Python to build scalable data pipelines while ensuring data quality and governance across all transformation stages.

Responsibilities include leveraging AI to optimize pipelines, coordinating with DevOps for platform deployment, and integrating validated products into analytics tools for