Location: Remote
Experience: 6 – 10 Years
Employment Type: Contract
Position Overview:
We are seeking a Data Engineer with strong expertise in Palantir Foundry and PySpark to join our data engineering team supporting reinsurance analytics. The ideal candidate will design and optimize scalable data pipelines, modernize ETL workflows, and enable data-driven insights for reinsurance business functions.
Key Responsibilities:
- Design, develop, and maintain robust data pipelines and ETL workflows using PySpark, SQL, and Palantir Foundry.
- Partner with data architects, business analysts, and actuarial teams to translate reinsurance data models into usable datasets.
- Build efficient ingestion, transformation, and validation processes for analytics and reporting.
- Leverage Palantir Foundry for workflow design, dataset management, and data governance.
- Ensure compliance with data security, quality, and governance standards.
- Identify and implement automation opportunities to improve data processes and performance.
Required Skills & Qualifications:
- 6–10 years of experience in data engineering or related roles.
- Strong hands-on skills in PySpark (DataFrames, RDDs, performance optimization).
- Proven experience with Palantir Foundry or similar data integration platforms.
- Solid understanding of reinsurance data structures (exposure, claims, policy).
- Proficiency in SQL, Python, and distributed data processing.
- Experience with cloud platforms (AWS, Azure, or GCP) and services like S3, Snowflake, or Databricks.
- Strong grasp of data modeling, metadata management, and governance frameworks.
- Familiarity with CI/CD, Git, and Agile delivery methodologies.
Preferred Skills:
- Experience with data warehousing and reporting modernization in the reinsurance domain.
- Exposure to Palantir ontology design and operationalization workflows.
- Knowledge of APIs, REST services, and event-driven architectures.
- Understanding of actuarial data, submission processes, and underwriting analytics.
