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Niche Palantir requirement reduces applicants, but mid-level data engineer title attracts moderate competition.
Palantir Foundry expertise and insurance domain preference limit cross-industry transferability.
Multiple mandatory technical skills and explicit 5–10 years experience increase filtering strictness.
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Design and build scalable and robust data pipelines and enterprise data models on Palantir Foundry platform.
Enable analytics and AI/ML use cases by integrating data pipelines with AI/ML frameworks and tools.
Develop interactive data applications using Foundry Workshop, Slate, and TypeScript-based custom frontends.
5-10 years of experience in data engineering with large-scale data pipelines and platforms.
2+ years of hands-on experience with Palantir Foundry including data ingestion, pipeline builder, and dataset management.
Proficiency in Python (3+ years), PySpark, TypeScript/JavaScript, and strong AWS services experience (S3, Glue, Athena, Lambda, Redshift).
Work Experience Required: 5+ years in Data Engineering, 2+ years with Palantir, 3+ years with Python
Experienced in working with microservices architecture and distributed systems relevant to data solutions.
Familiarity with DevOps practices including CI/CD, Docker, and Kubernetes for deployment and operationalization.
Prior exposure or strong interest in the insurance domain and experience with big data technologies like Snowflake is advantageous.