Data Engineer

Data Engineer

Chubb is a world leader in insurance. With operations in 54 countries and territories, Chubb provides commercial and personal property and casualty insurance, personal accident and supplemental health insurance, reinsurance and life insurance to a diverse group of clients. The company is defined by its extensive product and service offerings, broad distribution capabilities, exceptional financial strength and local operations globally. Parent company Chubb Limited is listed on the New York Stock Exchange (NYSE: CB) and is a component of the S&P 500 index. Chubb employs approximately 40,000 people worldwide.

Chubb launched its third Engineering Center in Thessaloniki in 2022. Our rapidly expanding new Chubb Engineering Center in Greece (CECG) is integrated with the Engineering Centers in India and Mexico to support our global technology needs and digital business transformation, as well as the company's operations in the Europe - Middle East - Africa region operating in 27 countries.

Overview

Chubb is looking for a Data Engineer to join our team. This is a permanent full-time position and a compelling opportunity to join a global, growing, financially stable and successful company. As an industry leader, Chubb is an employer of choice for skilled technology professionals aspiring to develop a meaningful career in a fast-paced, diverse company with offices in most major cities in the world.

Responsibilities:

• Implement well tested scalable data engineering solutions by following best practices and architectural principles while being responsible for all stages of the development lifecycle, from design and coding to integration, optimization, deployment, and support.
• Collaborate with stakeholders to understand data needs, capturing key insights in comprehensive documentation.
• Build and maintain scalable data infrastructure by provisioning cloud resources to support data processing and storage needs, following security and compliance standards.
• Organize, unify and optimize data from multiple structured and unstructured sources and environments to build robust, multi-functional data assets that support analytics.
• Develop high quality frameworks to enhance efficiency of the development processes ensuring uniformity of the data pipelines.
• Implement sophisticated data models that support multiple use cases across different products and domains.
• Solve exciting data engineering problems applying optimal ETL/ELT patterns and advanced query techniques.