Snowflake AWS Data Engineer

Snowflake AWS Data Engineer

4 to 9 years - Gurugram/Noida/Bangalore/Pune (hybrid)

P&C Insurance | Pricing, Rating & Actuarial Analytics

About the Role

We are looking for a Data Engineer to design, develop and maintain scalable data pipelines supporting P&C Insurance Pricing, Rating, Underwriting and Actuarial Analytics.

The ideal candidate will have strong hands-on expertise in SQL, Snowflake, Python and PySpark, along with 2+ years of P&C Insurance experience and an understanding of policy, claims, quote, coverage and pricing data.

You will work closely with Pricing Actuaries, Data Scientists, Business Analysts and Cloud Engineering teams to build high-quality data assets supporting predictive models, GLM pricing frameworks, rating updates, analytics and regulatory reporting.

Key Responsibilities

Data Engineering & Pipeline Development

• Design, develop and maintain scalable ETL/ELT pipelines using Python, PySpark and SQL.
• Build and optimize Snowflake-based data solutions for pricing and actuarial analytics.
• Develop reusable and parameterized data processing frameworks.
• Implement batch and incremental data ingestion pipelines.
• Develop data transformation logic supporting GLM, predictive pricing and rating models.

P&C Insurance Data Management

Work with and integrate data from:

• Policy Administration Systems
• Claims Systems
• Quote Data
• Vehicle & Driver Data
• Property Data
• Agency Data
• Third-party sources such as LexisNexis, Verisk, MVR and Credit Data
• Support pricing model development through data preparation and feature engineering.
• Partner with Actuarial and Underwriting teams to ensure accuracy of pricing inputs.

Snowflake & Cloud Engineering

• Develop optimized Snowflake SQL procedures, views, tasks and data marts.
• Perform performance tuning on large-scale datasets.
• Design data models supporting reporting, pricing analytics and ML use cases.
• Support migration of legacy EDW pipelines to modern Snowflake-based cloud platforms.

Data Quality & Governance

• Build automated data validation and reconciliation frameworks.
• Perform source-to-target mapping and maintain data lineage documentation.
• Develop monitoring and alerting mechanisms for pipeline health.
• Ensure adherence to enterprise data governance and regulatory standards.

Collaboration & Delivery

• Work within Agile teams to deliver data engineering solutions.
• Partner with Data Scientists to productionize feature pipelines and model refresh processes.
• Participate in code reviews, testing, deployment and CI/CD activities.
• Create technical documentation and operational runbooks.

Required Skills

Must Have

• Advanced SQL – 5+ years
• Snowflake – 3+ years
• Python – 3+ years
• PySpark / Spark SQL – 3+ years
• Strong Data Warehousing concepts
• ETL/ELT development
• Data Modeling
• Git / Version Control
• 2+ years of P&C Insurance experience

Insurance Domain Expertise

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

Good to Have

• Databricks
• AWS – S3, Glue, EMR, Lambda
• Airflow
• Jenkins
• Docker
• CI/CD
• Delta Lake / Iceberg
• REST APIs

Preferred Candidate Profile

The ideal candidate will have experience supporting:

• Insurance Pricing Model Development
• GLM Data Preparation
• Rating & Underwriting Analytics
• Large-scale Snowflake environments
• Feature Engineering / Feature Store
• Insurance Cloud Modernization
• Production-grade PySpark Pipelines
• Actuarial Analytics
• Policy and Claims Data

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Statistics, Mathematics, Data Science or a related field.
• Relevant certifications in AWS, Snowflake or Databricks are preferred.