The EU Amazon Vendor Services (AVS) and Retail Vendor Experience (VX) Program teams are seeking a Data Engineer to design and implement scalable data solutions and pipelines that can meaningfully contribute to both programs. This role is pivotal in addressing major challenges that enhance vendor success, satisfaction, and growth on Amazon, contributing directly to our long-term strategy.
Amazon's mission is to be Earth's most customer-centric company, where customers can discover anything they want to buy online at competitive prices, with vast selection and convenience. Core to this mission is our commitment to delighting not only customers but also vendors by inventing scalable solutions that exceed expectations. The EU AVS programme provides industry-leading account management services to vendors, optimising cost-to-serve and expediting their growth. The WW VX programme focuses on creating a globally preferred, trusted, and efficient vendor experience across all touchpoints. Both programmes are essential inputs for improving the end-customer experience and Amazon's long-term free cash flow.

Key job responsibilities
This role will sit within a data and analytics team supporting two large program teams (EU AVS and VX) while working closely with BIEs, scientists and 20+ Product Managers. As a Data and Applications Engineer, you will design, develop, and maintain scalable data pipelines and storage solutions to support analytical initiatives. Furthermore, you will build datasets and AI-powered applications to serve the analytical needs of AVS Growth Services including ProServe, a new retail consulting initiative for EU vendors.
Your primary responsibilities will include:
• Design and implement data pipelines and ETL processes to ingest, process, and manage structured and unstructured data at scale.
• Partner with PMs, BIEs and scientists to provide clean, production-ready datasets.
• Build and optimise data infrastructure to support the processing of structured and unstructured data.
• Automate processes for data collection, validation, and transformation to improve efficiency and accuracy across global vendor touchpoints.
• Build AI-enabled applications that empower both tech and non-tech data consumers at delivering bespoke insights.