FBS Data 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.

Job Summary The Life Data Platform (LDP) & Data Enablement team is responsible for acquiring, integrating, governing, modeling, and publishing enterprise data across on-premises and cloud platforms. The team enables trusted, scalable, and business-ready data products, analytics, reporting, and operational insights for Life Insurance functions through modern cloud-based data technologies and data engineering practices. The Data Engineer will be responsible for designing, developing, and supporting scalable data pipelines, data models, and enterprise data products that drive reporting, analytics, and operational business capabilities. This role combines hands-on data engineering with stakeholder engagement, working closely with business partners, analytics teams, technology teams, and external vendors to deliver high-quality data solutions and establish a trusted source of enterprise data.

Key Responsibilities Design, develop, and maintain scalable data pipelines and data integration solutions. Build and support enterprise data products for analytics, reporting, and operational use cases. Develop and maintain data models, data warehouses, and dimensional modeling solutions. Integrate data from internal systems, cloud platforms, APIs, and third-party vendors. Collaborate with business stakeholders to gather requirements and translate business needs into technical solutions. Ensure data quality, governance, reliability, and consistency across platforms. Optimize SQL queries and data processing performance. Support cloud-based data platforms and modern data engineering frameworks. Partner with external vendors and cross-functional teams to deliver successful data initiatives. Provide technical leadership, mentoring, and guidance on data engineering best practices. Support project planning, estimation, and execution in Agile environments. Drive continuous improvements in data architecture, automation, and data platform capabilities.