Empiric
Palantir Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Palantir Data Engineer with 6-10 years of experience, focusing on PySpark and reinsurance data. The contract lasts 3-6 months, offers $70-$75 per hour, and is remote. Key skills include SQL, Python, and cloud platforms.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
600
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🗓️ - Date
November 11, 2025
🕒 - Duration
3 to 6 months
-
🏝️ - Location
Remote
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
United States
-
🧠 - Skills detailed
#Security #Data Lineage #Spark (Apache Spark) #Databricks #Data Architecture #"ETL (Extract #Transform #Load)" #Metadata #SQL (Structured Query Language) #Automation #Data Engineering #Agile #Data Integration #Business Analysis #AWS (Amazon Web Services) #Datasets #Data Governance #Spark SQL #Cloud #Data Ingestion #PySpark #Python #GCP (Google Cloud Platform) #GIT #REST services #Data Management #Snowflake #S3 (Amazon Simple Storage Service) #Palantir Foundry #Azure #Data Pipeline #REST (Representational State Transfer) #Data Security #Compliance #Data Modeling #Version Control
Role description
Palantir Data Engineer - PySpark - Insurance Experience
Contract: 3-6 months initial
Rate: $70-$75 per hour
Location: Remote
Job Description:
• Develop, design, and sustain data pipelines and ETL workflows using PySpark, SQL, and Palantir Foundry.
• Partner with data architects, business analysts, and actuarial teams to grasp reinsurance data models and convert intricate datasets into accessible formats.
• Create and enhance processes for data ingestion, transformation, and validation to support analytical and reporting objectives.
• Utilize the Palantir Foundry platform to craft robust workflows, manage datasets, and guarantee efficient data lineage and governance.
• Uphold data security, compliance, and governance in accordance with industry standards and client requirements.
• Spot opportunities for automation and process enhancements across data systems and integrations.
Required Skills & Qualifications:
• 6 to 10 years of experience in data engineering roles.
• Strong practical knowledge of PySpark (including dataframes, RDDs, and performance optimization).
• Demonstrated experience with Palantir Foundry or comparable data integration platforms.
• Solid understanding of reinsurance, including exposure, claims, and policy data structures.
• Proficiency in SQL and Python, along with experience handling large datasets in distributed environments.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and their associated data services (e.g., S3, Snowflake, Databricks).
• Knowledge of data modeling, metadata management, and data governance frameworks.
• Experience with CI/CD pipelines, version control systems (Git), and Agile delivery methodologies.
Preferred Skills:
• Experience in data warehousing and reporting modernization projects within the reinsurance sector.
• Familiarity with Palantir ontology design and data operationalization.
• Working knowledge of APIs, REST services, and event-driven architecture.
• Understanding of actuarial data flows, submission processes, and underwriting analytics is a plus.
Palantir Data Engineer - PySpark - Insurance Experience
Contract: 3-6 months initial
Rate: $70-$75 per hour
Location: Remote
Job Description:
• Develop, design, and sustain data pipelines and ETL workflows using PySpark, SQL, and Palantir Foundry.
• Partner with data architects, business analysts, and actuarial teams to grasp reinsurance data models and convert intricate datasets into accessible formats.
• Create and enhance processes for data ingestion, transformation, and validation to support analytical and reporting objectives.
• Utilize the Palantir Foundry platform to craft robust workflows, manage datasets, and guarantee efficient data lineage and governance.
• Uphold data security, compliance, and governance in accordance with industry standards and client requirements.
• Spot opportunities for automation and process enhancements across data systems and integrations.
Required Skills & Qualifications:
• 6 to 10 years of experience in data engineering roles.
• Strong practical knowledge of PySpark (including dataframes, RDDs, and performance optimization).
• Demonstrated experience with Palantir Foundry or comparable data integration platforms.
• Solid understanding of reinsurance, including exposure, claims, and policy data structures.
• Proficiency in SQL and Python, along with experience handling large datasets in distributed environments.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and their associated data services (e.g., S3, Snowflake, Databricks).
• Knowledge of data modeling, metadata management, and data governance frameworks.
• Experience with CI/CD pipelines, version control systems (Git), and Agile delivery methodologies.
Preferred Skills:
• Experience in data warehousing and reporting modernization projects within the reinsurance sector.
• Familiarity with Palantir ontology design and data operationalization.
• Working knowledge of APIs, REST services, and event-driven architecture.
• Understanding of actuarial data flows, submission processes, and underwriting analytics is a plus.
