National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Data Engineer, EU AVS/VX

Redefined Ltd
London
1 week ago
Create job alert

DESCRIPTION
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)
    Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
    Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
    Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit

    https://amazon.jobs/content/en/how-we-hire/accommodations

    for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

    #J-18808-Ljbffr

Related Jobs

View all jobs

Software/Data Engineer - Commodities Desk...

Software/Data Engineer - Commodities Desk...

Data Engineer

Data Engineer - Water Sector

Data Engineer - Water Sector

Pyspark Data Engineer

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.