Job Title: Data Engineer - P&C; Insurance & Analytics (Snowflake / PySpark)

Summary: EXL Analytics is looking for a skilled Data Engineer with 3+ years of technical experience and 2+ years of Property & Casualty (P&C;) insurance domain expertise to design, develop, and maintain scalable data pipelines. The role focuses on powering P&C; pricing, rating, underwriting, and actuarial analytics through Snowflake, PySpark, Python, and SQL, directly serving predictive pricing frameworks and enterprise cloud modernization initiatives.

Location: India (Flexible / Hybrid depending on organizational guidelines)

Your Future Employer: EXL (NASDAQ: EXLS) is a leading operations management and analytics company headquartered in New York, with over 24,000 professionals globally. EXL Analytics leverages proprietary frameworks, cutting-edge analytics, and cloud technologies to transform decision-making for top global industries.

Responsibilities:

Design, build, and optimize scalable ETL/ELT pipelines using Python, PySpark, SQL, and Snowflake to support GLM pricing frameworks and predictive actuarial models.

Integrate P&C; data across policy administration, claims, quote, property, vehicle, driver, and third-party sources (e.g., LexisNexis, Verisk, MVR) for feature engineering and model preparation.

Develop optimized Snowflake SQL procedures, views, tasks, and data marts while leading performance tuning and data modeling efforts.

Implement automated data quality validation, reconciliation frameworks, source-to-target mapping, data lineage, and pipeline monitoring controls.

Partner with Pricing Actuaries, Data Scientists, and Cloud Engineers in Agile teams to productionize feature stores, model refreshes, and CI/CD pipelines.

Requirements:

Bachelor's or Master's degree in Computer Science, Engineering, Statistics, Mathematics, Data Science, or a related field.

5+ years of Advanced SQL experience alongside 3+ years of hands-on experience in Snowflake, Python, and PySpark / Spark SQL.





Mandatory 2+ years of domain experience in Property & Casualty (P&C;) Insurance, including Personal Auto, Homeowners, or Commercial Lines.

Strong understanding of policy/claims data structures, actuarial data flows, GLM-based pricing models, and underwriting datasets.

Practical knowledge of Data Warehousing concepts, data modeling, Git version control, and cloud platforms (AWS, Databricks, or Airflow preferred).

What is in it for you:

Opportunity to work directly alongside world-class analytics consultants and data scientists in a fast-paced, cutting-edge environment.

Robust learning and development opportunities backed by heavy investments in training for analytical tools and techniques.

Structured mentorship program pairing junior employees with senior leaders to guide professional growth and career advancement.

Reach us: If you think this role is aligned with your career, kindly write me an email along with your updated CV on [Insert Email Address] for a confidential discussion on the role.

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