Design, build, and maintain scalable cloud-based ETL/ELT data pipelines (Python, PySpark, SQL, Snowflake) supporting P&C insurance pricing, rating, underwriting, and actuarial analytics. Collaborate with actuaries, data scientists, analysts, and cloud engineers to deliver reusable data frameworks, batch/incremental ingestion, data quality, and transformations for GLM and predictive models.
- We are seeking a highly skilled Data Engineer to design, develop, and maintain scalable data pipelines supporting Property & Casualty (P&C) Insurance Pricing, Rating, Underwriting, and Actuarial Analytics. The ideal candidate will have strong expertise in SQL, Snowflake, PySpark, and Python, coupled with insurance domain knowledge across policy, claims, quote, coverage, and pricing datasets.
- The candidate will work closely with Pricing Actuaries, Data Scientists, Business Analysts, and Cloud Engineering teams to deliver high-quality data assets that power predictive models, GLM pricing frameworks, rating updates, analytics, and regulatory reporting. The role involves building modern cloud-based ETL/ELT pipelines, optimizing large-scale data processing, implementing data quality frameworks, and supporting enterprise data modernization initiatives.
- Data Engineering & Pipeline Development
- Design, develop, and support scalable ETL/ELT pipelines using Python, PySpark, and SQL.
- Build and optimize Snowflake-based data solutions for pricing and actuarial analytics.
- Create reusable and parameterized data processing frameworks.
- Implement batch and incremental data ingestion pipelines.
Develop data transformation logic supporting GLM, predictive pricing, and rating models
QualificationsBachelor's or Master's degree in Computer Science, Engineering, Statistics, Mathematics, Data Science, or a related field.
Relevant Cloud Certifications (AWS, Snowflake, Databricks) preferred
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