Join Amazon's EU Hardlines analytics team as a Senior Business Intelligence Engineer where you'll shape the future of online shopping through data-driven insights. This role combines Customer Experience analysis with Item Data Quality innovation to improve how millions discover and shop for products. You'll be part of a technical team of four Business Intelligence Engineers and one Research Specialist, driving data innovation across Amazon's European stores.
The position offers a unique opportunity to investigate the full customer journey through deep-dive reports and comprehensive analysis. Working with product managers, you'll analyze everything from search patterns to product discovery behaviors, visualization feature adoption, and detail page engagement. You'll build automated reporting solutions, design and analyze experiments, and create sophisticated dashboards that drive decisions.
The team operates across two key charters: Marketing Analytics and Customer Experience (CX) & Item Data Quality (IDQ). Your work will span multiple technical disciplines, from deep-dive analytics using SQL and Spark SQL for large-scale data processing, to building automated marketing solutions with Python, Lambda, React.js, and leveraging internal personalization toolkits.
You'll have the opportunity to create lasting impact at scale, working with best-in-class tools to build automation solutions that transform how teams work. Your analysis and recommendations will influence strategic decisions and drive real improvements to the shopping experience for millions of European customers. The team maintains a strong culture of innovation where technical excellence meets customer obsession.
The role is available in any of the core EU5 offices: London, Paris, Munich, Madrid, or Milan, offering flexibility in location while working with cross-functional teams across Europe. You'll be part of a team that has established itself as the automation and measurement powerhouse in EU Stores, with solutions enabling thousands of marketing experiences and saving significant operational time through automated campaign scheduling, storefront creation, and performance measurement.