Foundry Platform Engineer — AI-Driven ETL Pipelines

Devopsroles; Herndon, Northern (VA, KY); Hybrid; USD 150,000 - 250,000; Full time

Job summary

GRVTY in Herndon, VA is seeking a Palantir Platform Engineer with TS/SCI + Poly clearance to join a critical project. You will integrate custom ETL workflows within Palantir, connect ETL conditioners to Palantir tooling, and enhance observability across data transformations.

You will design and build robust PySpark and Python data pipelines, apply AI to optimize processing of large datasets, and ensure data governance, validation, and quality as products move toward advanced analytics.

Qualifications

• Active TS/SCI with Polygraph clearance.
• 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.

Responsibilities

• Integrate and optimize custom ETL workflows within Palantir ecosystem.
• Connect ETL conditioners to Palantir tooling to improve observability.
• Design and implement robust PySpark/Python data pipelines for large datasets.
• Apply AI techniques to accelerate data processing and insights.
• Support data governance, validation, and quality as products move to analytics tools.

Skills

TS/SCI clearance

Palantir Foundry

Ontology knowledge

ETL pipelines

PySpark

Python

Logging/Monitoring

Data governance

DevOps

AI for data pipelines

Data product validation

Tools

Palantir Foundry

Job description

GRVTY in Herndon, VA is seeking a Palantir Platform Engineer with TS/SCI + Poly clearance to join a critical project. You will integrate custom ETL workflows within Palantir, connect ETL conditioners to Palantir tooling, and enhance observability across data transformations.

You will design and build robust PySpark and Python data pipelines, apply AI to optimize processing of large datasets, and ensure data governance, validation, and quality as products move toward advanced analytics.