We are seeking an experienced and dynamic Data Engineer to join our team. This critical role will focus on designing and implementing automated data solutions, driving operational efficiency, and enhancing data scalability across the organization. The ideal candidate will possess a deep understanding of data engineering principles, experience in developing flexible and scalable data frameworks, and a commitment to best practices in data management.
Location: London, UK
Key Responsibilities:
Collaborate with stakeholders to devise solutions and designs for upcoming projects associated with EMEA/LATAM regions and any 360 expansion initiatives. Evaluate project requirements and develop architecture designs that support the specific needs of these regions and expansion efforts. Ensure that solutions are scalable and adaptable to diverse business environments. Evaluate current manual data processes to uncover opportunities for automation within the Smart Data Management ecosystem. Develop optimized automated data pipelines and workflows to streamline data integration, transformation, and availability. Ensure efficient monitoring and notification systems for data pipeline success or failure to enhance operational efficiency. Sourcing data from multiple applications, profiling, cleansing and conforming to create master data sets for analytics use. Create a common, flexible, and scalable data framework applicable to various data projects and analytics initiatives. Establish standardized data components, design patterns, and methodologies to enhance data engineering project delivery speed and efficiency. Collaborate with data analysts and scientists to adapt the framework to meet unique data requirements while maintaining scalability. Leverage extensive experience to enforce data engineering best practices throughout the development lifecycle. Ensure that data solutions are standardized, maintainable, and reliable for long-term operational support. Conduct code reviews and provide technical guidance to data engineering teams on best practices. Assess existing data processes and workflows to identify limitations and areas for improvement. Recommend actionable solutions to optimize data efficiency, enhance data quality, and reduce operational costs. Promote a culture of innovation by exploring emerging technologies and methodologies that can enhance data engineering practices. Propose and pilot innovative data solutions that challenge conventional data management approaches and enable new ways of leveraging data. Collaborate with cross-functional teams to drive the adoption of innovative technologies across the data landscape. Continuously research and stay updated on the latest data engineering technologies and industry trends. Evaluate and integrate suitable technologies into existing data solutions to enhance organizational competitiveness and adaptability.
Qualifications:
Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field; Master’s degree preferred. A minimum of 5+ years of experience as a Data Engineer or in a related role, with a focus on automation and data process improvement. Demonstrated experience in designing and implementing automation frameworks and solutions for data pipelines and transformations. Strong understanding of data processing frameworks (., Apache Spark, Apache Kafka) and database technologies (., SQL, NoSQL). Expertise in programming languages relevant to data engineering (., Python, SQL). Hands on data preparation activities using the Azure technology stack especially Azure, Databricks, Snowflake is strongly preferred. Experience with Web Scraping frameworks (Scrapy or Beautiful Soup or similar) Familiarity with cloud data platforms (., AWS, Azure, Google Cloud) is a plus. Hands on experience required with Airflow/Astronomer, DBT. Practical knowledge on Graph and Vector DB Excellent problem-solving skills and ability to think strategically about data and its role in improving organizational efficiency. Strong communication, collaboration, and leadership skills, with the ability to work effectively across departments and with stakeholders at all levels. Databricks Spark and Microsoft Azure certifications are plus.
About Us
Chubb is a world leader in insurance. With operations in 54 countries, 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 distinguished by its extensive product and service offerings, broad distribution capabilities, exceptional financial strength, underwriting excellence, superior claims handling expertise and local operations globally.
At Chubb, we are committed to equal employment opportunity and compliance with all laws and regulations pertaining to it. Our policy is to provide employment, training, compensation, promotion, and other conditions or opportunities of employment, without regard to race, color, religious creed, sex, gender, gender identity, gender expression, sexual orientation, marital status, national origin, ancestry, mental and physical disability, medical condition, genetic information, military and veteran status, age, and pregnancy or any other characteristic protected by law. Performance and qualifications are the only basis upon which we hire, assign, promote, compensate, develop and retain employees. Chubb prohibits all unlawful discrimination, harassment and retaliation against any individual who reports discrimination or harassment.
