FBS - Associate Analytics Engineer

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 large-scale datasets.
• Strong problem-solving skills and ability to identify data quality issues.

Preferred Qualifications

• Snowflake
• Apache Airflow
• Databricks
• Exposure to Machine Learning environments
• Experience supporting data architecture modernization or migration initiatives
• Previous Analytics Engineering experience

Ideal Candidate

You are a curious and collaborative data professional who enjoys solving complex data challenges and building scalable solutions. You excel at working across teams, connecting information from different business areas, and continuously identifying opportunities to improve data quality, accessibility, and operational efficiency.

Why Join Us?

• Work on high-impact initiatives supporting actuarial and insurance analytics.
• Help shape and modernize a growing data ecosystem.
• Collaborate with Data Engineering, Analytics, and Data Science teams.
• Gain exposure to cloud technologies, modern data platforms, and advanced analytics projects.

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 wit...

Python
SQL
Great Level of English

Pipeline Managment

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 large-scale datasets.
• Strong problem-solving skills and ability to identify data quality issues.

Preferred Qualifications

• Snowflake
• Apache Airflow
• Databricks
• Exposure to Machine Learning environments
• Experience supporting data architecture modernization or migration initiatives
• Previous Analytics Engineering experience

Ideal Candidate

You are a curious and collaborative data professional who enjoys solving complex data challenges and building scalable solutions. You excel at working across teams, connecting information from different business areas, and continuously identifying opportunities to improve data quality, accessibility, and operational efficiency.

Why Join Us?

• Work on high-impact initiatives supporting actuarial and insurance analytics.
• Help shape and modernize a growing data ecosystem.
• Collaborate with Data Engineering, Analytics, and Data Science teams.
• Gain exposure to cloud technologies, modern data platforms, and advanced analytics projects.

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 wit...

Python
SQL
Great Level of English

Pipeline Managment