Manager

Description 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. Qualifications Qualifications • Bachelor's or Master's degree in Computer Science, Engineering, Statistics, Mathematics, Data Science, or a related field. • Relevant Cloud Certifications (AWS, Snowflake, Databricks) preferred. • Preferred • 2+ years of experience in Property & Casualty (P&C) Insurance • Strong Understanding Of • Personal Auto Insurance • Homeowners Insurance • Commercial Lines • Pricing & Rating Analytics • GLM-based Pricing Models • Underwriting Data • Policy & Claims Data Structures • Actuarial Data Flows Preferred Candidate Profile • The ideal candidate has experience supporting: • Pricing model development • GLM data preparation • Rating and underwriting analytics • Large-scale Snowflake environments • Feature store development • Insurance cloud modernization initiatives • Production-grade PySpark pipelines • Keywords: SQL, Snowflake, Python, PySpark, Data Engineering, ETL, ELT, AWS, Databricks, Pricing Analytics, GLM, Personal Auto, Homeowners, Policy Data, Claims Data, Insurance Data Warehouse, Feature Engineering, Actuarial Analytics. Required Technical SkillS • Advanced SQL (5+ years) • Snowflake (3+ years) • Python (3+ years) • PySpark / Spark SQL (3+ years) • Data Warehousing Concepts • ETL/ELT Development • Data Modeling • Git Version Control • Preferred • Databricks • AWS (S3, Glue, EMR, Lambda) • Airflow • Jenkins • Docker • CI/CD Frameworks • Delta Lake / Iceberg • REST APIs