On-siteSeniorData Engineerposted 3w ago

✦Role summaryAI-generated

This Data Engineer will design and maintain scalable cloud-based ETL/ELT pipelines for Property & Casualty insurance data, leveraging SQL, Snowflake, PySpark, and Python to support pricing, rating, and actuarial analytics. The role collaborates with actuaries, data scientists, and cloud engineers to implement data quality frameworks and optimize large-scale processing for regulatory reporting and predictive modeling.

Skills required

SQL Snowflake Spark Python ETL ELT Data pipelines Data quality Cloud computing Data engineering Data transformation Statistics Data science AWS Databricks

About this role

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.

Responsibilities

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