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Mid-level generalist data role in a metro but Palantir specialization narrows candidate pool.
Palantir Foundry requirement and insurance domain preference reduce cross-industry transferability.
Multiple mandatory filters: 5-10 years, 2+ years Palantir, Python/PySpark and AWS experience.
Design and build scalable data pipelines and enterprise data models using Palantir Foundry.
Develop interactive data applications using Foundry Workshop, Slate, and custom frontends with TypeScript.
Enable analytics and AI/ML use cases by integrating data engineering solutions with AI/ML frameworks on cloud platforms.
5-10 years of overall experience in data engineering and building large-scale data platforms.
2+ years of hands-on experience with Palantir Foundry, including data ingestion and pipeline building.
Proficiency in Python (3+ years), PySpark, TypeScript/JavaScript, and experience with AWS data services (S3, Glue, Athena, Lambda, Redshift).
Work Experience Required: 5+ years in Data Engineering; 2+ years with Palantir; 3+ years with Python; Insurance domain experience is a plus but not mandatory.
Experienced in microservices architecture and distributed systems supporting data platforms.
Familiar with AI/ML toolkits integration (TensorFlow, PyTorch) and deployment via modern DevOps practices (CI/CD, Docker, Kubernetes).
Prefer candidates with Palantir Foundry certification or demonstrated project experience and prior insurance domain exposure.