Job Overview

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Senior Business Intelligence Engineer – Base location: Madrid or Berlin.

We’re looking for someone passionate about using data to create shopping experiences that feel genuinely personal. You will lead the building and scaling of personalised recommendations for millions of customers across ten European marketplaces.

In this role, you sit at an intersection of business intelligence, data engineering, and data science. You will build on Amazon’s world‑class personalisation infrastructure to consume real‑time customer intent signals, blend them with large‑scale EU retail data and engagement metrics, and apply custom processors and matching models to surface the right product at the right moment. You will design complement strategies that inspire follow‑on purchases, discovery strategies that introduce customers to new categories, and inspiration experiences that tap into individual browsing and purchase patterns – layered on top of centralised recommendation systems and enriched with EU‑specific intelligence that you build and own.

On the data science side, you will develop custom models using Python and Spark to understand customer‑product affinity at scale—applying techniques like embeddings modelling and customer persona matching—to power EU‑specific personalisation strategies built on top of Amazon’s integral recommendation infrastructure.

On the engineering side, you will build and deploy the internal tooling that puts these capabilities directly in the hands of marketing teams – writing production‑grade Python services, building serverless infrastructure with AWS Lambda and CDK, and developing APIs with FastAPI.

Analytics sits alongside both: you’ll own the baseline reporting and measurement suite for personalised marketing campaigns, powered by models built across the broader team, and use those insights to deep‑dive into customer engagement, quantify the impact of strategies across homepage experiments, storefronts, and seasonal events, and continuously drive improvements that matter.

We expect you to take genuine ownership of your domain, spot gaps, and act proactively. You should have a strong appetite for picking up new technologies and getting them into production quickly, whether it’s a new AWS service, an emerging data science technique, or an internal platform you’ve never touched before.



You should also be genuinely excited about the pace of change in this space – not just keeping up with it, but staying ahead and bringing fresh ideas to the team.

Key Responsibilities

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- Leading the design and delivery of personalised recommendation strategies for EU customers, combining large‑scale Amazon retail data, real‑time customer signals, and custom models to surface the right products at the right moment.

- Developing custom data models using Python and Spark, applying techniques such as embeddings modelling and customer persona matching to power EU‑specific personalisation strategies built on top of Amazon’s global recommendation infrastructure.

- Designing, developing, and maintaining internal tooling and services that enable marketing teams to independently configure and launch personalised campaigns – Python based serverless applications (AWS Lambda) with React front ends.

- Owning the baseline reporting and measurement suite for personalised marketing campaigns, building standardised metrics and dashboards in collaboration with the broader team to track performance across all channels and surfaces.

- Conducting deep‑dive analytics to understand drivers of customer engagement and personalisation performance, translating findings into concrete strategic and technical recommendations.

- Writing advanced SQL and leveraging big data query engines to extract, transform, and analyse large‑scale datasets across Amazon’s data ecosystem, forming the analytical foundation for personalisation strategies and campaign reporting.

- Partnering and collaborating closely with colleagues across the EU Customer Insights and Analytics team, contributing expertise across the full analytical and engineering stack.

About The Team

We are the EU Stores Customer Experience Analytics & Automation team – simultaneously a product team, a data science team, and a customer analytics team. Our mission is to transform Amazon’s vast selection into curated, personalised, shoppable experiences that help customers find products they’ll love.

The BIE function sits at the technical core of that mission. We build the data primitives, automation systems,



and self‑service platforms that make personalised discovery at scale possible. Where global teams provide foundational building blocks, we build orchestration layers on top – composing capabilities into workflows tailored to EU requirements. Where gaps exist, we close them. Where central solutions mature, we converge and evolve.

Our work spans three areas: data models and pipelines powering personalised recommendations across EU10; production applications used by hundreds of marketing stakeholders daily, built with Python, React, Lambda, FastAPI, and CDK; and CX analytics across search, detail page, and marketing that tells leadership whether it’s working.

We write production code, design systems others depend on, and analyse data that shapes strategic decisions. If you want to do serious work at the intersection of data, product, and customer experience – this is the place.

Basic Qualifications

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- Experience programming to extract, transform and clean large (multi‑TB) data sets.

- Experience with theory and practice of design of experiments and statistical analysis of results.

- Experience with AWS technologies.

- Experience in scripting for automation (e.g., Python) and advanced SQL skills.

- Experience with theory and practice of information retrieval, data science, machine learning and data mining.

- Experience working directly with business stakeholders to translate between data and business needs.

- Experience with SQL.

- Experience with data visualization using Tableau, Quicksight, or similar tools.

- Experience in the data/BI space.

Preferred Qualifications

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- Experience building machine learning models or developing algorithms for business application.

- Experience working on and delivering end‑to‑end projects independently.

- Experience with designing and building applications using AWS services such as Lambda, AWS Elastic Beanstalk, Kubernetes.

- Experience in data applications using large‑scale distributed systems (e.g., EMR, Spark, Elasticsearch, Hadoop, Pig, and Hive).

Equal Opportunity Statement

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. xcskxlj Protecting your privacy and the security of your data is a longstanding top priority for Amazon.

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📌 Senior Business Intelligence Engineer, EU Stores CX Analytics & Automation (Madrid)
🏢 Amazon
📍 Madrid