Amazon EU SARL (UK Branch)

E-commerce

Sr.DataEngineer,EUBooksAnalyticsandEngineering

£95–145k ~AI est. London, England, United Kingdom FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Sr. Data Engineer, EU Books Analytics and Engineering at Amazon EU SARL (UK Branch). Skills: Data Engineering, Data Architecture, ETL Pipelines, Data Modeling. Own and evolve team-level data architecture. Design and build scalable data pipelines”

What You'll Achieve.

Reduce stakeholder dependence on manual BI work; Enable self-service access at scale

Industry & Context.

E commerce
Problems you'll solve

Break complex problems

What They're Looking For.

Must Have

Experience with data modeling, Experience with warehousing, Experience building ETL pipelines, Experience with SQL, Experience in at least one modern scripting or programming language, Experience mentoring team members

Nice to Have

Experience communicating with users, Experience communicating with technical teams, Experience communicating with management, Experience describing data modeling decisions, Experience describing data engineering strategy, Experience providing technical leadership, Experience mentoring other engineers, Knowledge of distributed systems, Experience building highly available systems, Experience operating highly available systems, Experience building distributed systems, Experience operating distributed systems, Experience with data extraction, Experience with data ingestion, Experience with data processing of large data sets

What You'll Do.

Own and evolve team-level data architecture

Design and build scalable data pipelines

Integrate business signals from diverse sources

Define data models and schemas

Build automated data quality frameworks

Engineer self-service data access

Build measurement infrastructure for business experiments

Drive cost optimization

Drive data governance

Partner with business stakeholders

Partner with cross-functional teams

Translate analytical requirements into data solutions

Contribute to AI Engineering roadmap

Build data backbone for AI applications

Break complex cross-domain problems

Coordinate delivery across contributors

How You'll Work.

Team & Collaboration

Cross-functional teams; Business stakeholders; BI engineers

Communication Scope

Translate analytical requirements

Process & Methodology

Workstreams

Full Job Description

Amazon EU Books serves millions of customers across European markets with one of the world's largest book selections, spanning Kindle, print, and audiobook formats. The EU Books BI and Data Engineering team is transforming from a traditional reporting function into an AI-enabled decision intelligence engine. We are building the data foundation that powers self-service analytics, predictive models, and domain-specific AI applications across the EU Books organization. We are looking for a Data Engineer III to own and evolve the data architecture that supports multiple business domains including Demand, Pricing, Deals, Finance, and EU Books Leadership. You will build the infrastructure layer that connects raw business signals into reliable, governed, model-ready datasets, enabling both operational reporting and the advanced analytics capabilities we are building toward. The current data landscape spans multiple systems, teams, and marketplaces. You will consolidate, govern, and automate it, reducing stakeholder dependence on manual BI work and enabling self-service access at scale. Key job responsibilities - Own and evolve team-level data architecture: ingestion, transformation, storage, serving, and monitoring across multiple EU marketplaces and business domains - Design and build scalable, self-healing data pipelines that integrate business signals from diverse sources (demand, pricing, customer behavior, operational metrics) - Define data models and schemas optimized for both operational reporting and statistical/econometric model consumption - Build automated data quality frameworks that ensure accuracy and reliability for high-stakes business decisions - Engineer self-service data access through metadata-rich catalogs, governed query layers, and dashboard-ready datasets that enable stakeholders to answer recurring questions without BI mediation - Build the measurement infrastructure for business experiments (A/B tests, weblabs), ensuring clean experiment data and

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