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 15+ Product Managers. As a Data Engineer, you will design, develop, and maintain highly scalable data pipelines and storage solutions to support advanced analytics, machine learning (ML), and artificial intelligence (AI) initiatives. You will be instrumental in ensuring the availability, reliability, and scalability of data systems that drive insights and actions for the AVS Growth Services programme.
Your primary responsibilities will include:
•Data Architecture & Pipelines: Design and implement data pipelines and ETL processes to ingest, process, and manage structured and unstructured vendor feedback data at scale.
• Collaborative Development: Partner with BIEs and scientists to provide clean, production-ready datasets.
• Scalable Solutions: Build and optimise data infrastructure to support the processing of structured and unstructured vendor data.
• Insights & Reporting: Create robust systems for monitoring and reporting on key metrics, enabling cross-functional teams.
• Automation: Automate processes for data collection, validation, and transformation to improve efficiency and accuracy across global vendor touchpoints.
BASIC QUALIFICATIONS
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience as a Data Engineer or in a similar role
PREFERRED QUALIFICATIONS
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
