Keylent Inc
Palantir Foundry Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Palantir Foundry Engineer with a contract length of "X months" and a pay rate of "$X per hour." Key skills include PySpark, SQL, and ETL processes, with a focus on reinsurance data models and data governance.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
November 11, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#Palantir Foundry #Security #Business Analysis #Data Lineage #Spark (Apache Spark) #Data Security #Compliance #Datasets #SQL (Structured Query Language) #Spark SQL #Data Ingestion #PySpark #Data Architecture #"ETL (Extract #Transform #Load)" #Automation #Data Pipeline
Role description
• Design, develop, and maintain data pipelines and ETL workflows using PySpark, SQL, and Palantir Foundry.
• Collaborate with data architects, business analysts, and actuarial teams to understand reinsurance data models and transform complex datasets into usable formats.
• Build and optimize data ingestion, transformation, and validation processes to support analytical and reporting use cases.
• Work within the Palantir Foundry platform to design robust workflows, manage datasets, and ensure efficient data lineage and governance.
• Ensure data security, compliance, and governance in line with industry and client standards.
• Identify opportunities for automation and process improvement across data systems and integrations.
• Design, develop, and maintain data pipelines and ETL workflows using PySpark, SQL, and Palantir Foundry.
• Collaborate with data architects, business analysts, and actuarial teams to understand reinsurance data models and transform complex datasets into usable formats.
• Build and optimize data ingestion, transformation, and validation processes to support analytical and reporting use cases.
• Work within the Palantir Foundry platform to design robust workflows, manage datasets, and ensure efficient data lineage and governance.
• Ensure data security, compliance, and governance in line with industry and client standards.
• Identify opportunities for automation and process improvement across data systems and integrations.
