Our Client is one of the United States' largest insurers, providing a wide range of insurance and financial services products with gross written premiums well over US$25 Billion (P&C;). They proudly serve more than 10 million U.S. households with more than 19 million individual policies across all 50 states through the efforts of over 48,000 exclusive and independent agents and nearly 18,500 employees. Finally, our Client is part of one the largest Insurance Groups in the world.

About The Role

We are seeking an Analytics Engineer to join our Actuarial & Insurance team and play a key role in modernizing and enhancing our data architecture. This position serves as a bridge between Data Engineering, Analytics, and Data Science, ensuring that high-quality, reliable data is available to support reporting, advanced analytics, and business decision-making.

This is a highly technical, hands-on role focused on building and maintaining data pipelines, transforming and validating data, and improving data accessibility across the organization.

Key Responsibilities

Build, maintain,



and optimize data pipelines and data workflows
Clean, transform, and validate large datasets from multiple sources
Support the modernization of data architecture and platform capabilities
Manage and maintain data assets within cloud-based environments
Ensure data quality, integrity, and accessibility for analytics and reporting
Collaborate with Data Engineers, Analysts, Data Scientists, and business stakeholders
Identify data gaps and implement solutions that improve reliability and efficiency

Required Qualifications

3+ years of experience in Analytics Engineering, Data Engineering, or related roles
Strong Python programming skills
Advanced SQL expertise
Experience building and maintaining data pipelines
Hands-on experience with data transformation, cleansing, and validation
Experience with Data Warehousing concepts and technologies
AWS experience, particularly with S3
Experience working with la

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