About the Role
We are seeking an experienced Palantir Platform Engineer in Herndon, VA. In this role, you will play a pivotal role in integrating custom ETL workflows within the Palantir ecosystem. You will be responsible for connecting ETL conditioners to Palantir tooling, driving enhanced observability, and accelerating data conditioning efforts.

Your expertise will ensure that stakeholders maintain comprehensive, end-to-end insight into each phase of the transformation process. Leveraging your skills in PySpark, Python, and modern data governance, you will design and implement robust data pipelines, harness AI to optimize data processing, and prepare reliable data products for seamless integration into advanced analytics tools.

Key Responsibilities
ETL Pipeline Engineering: Design, build, and optimize scalable ETL workflows and data pipelines using Python and PySpark to support seamless data flow and transformation.

Tooling & Observability Integration: Connect custom ETL conditioners to Palantir tooling to maximize system observability, accelerate data conditioning, and ensure visibility across every phase of data transformation.

Ontology & Governance: Leverage deep understanding of data ontology modeling, logging, and monitoring frameworks to maintain high standards of data governance, validation, and data quality.

AI-Driven Optimization: Harness artificial intelligence and machine learning capabilities to augment and optimize data pipelines, driving greater speed and efficiency when processing large-scale datasets.

Deployment & Collaboration: Manage operational and deployment aspects using DevOps practices, collaborating closely with cross-functional teams to deliver secure, actionable data insights and exploitable analytics products.

Required Skills & Qualifications
Security Clearance: Active TS/SCI with Polygraph clearance required.

Palantir Ecosystem: Hands-on experience with Palantir Foundry.

Data Architecture: Strong, demonstrable understanding of Data Ontology and ontology modeling.

ETL Expertise: Proven expertise in building, scaling, and integrating complex ETL pipelines.

Programming Languages: Proficiency in Python and PySpark.

Operations & Observability: Experience with logging, monitoring solutions, and DevOps methodologies.

Governance & Quality: Knowledge of data governance best practices and strong skills in data product validation.

Preferred Skills & Experience
Specialized experience connecting ETL conditioners directly to Palantir tooling.

A proven background in increasing system observability and accelerating data conditioning workflows.

Demonstrated success in ensuring comprehensive, end-to-end stakeholder insight into data transformation processes.

Experience integrating rigorously validated data products into advanced analytics tools for deep data exploitation.