Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Business Intelligence Engineer, DNA

Amazon.com, Inc
London
4 days ago
Create job alert
Overview

Our team is looking for an experienced Senior Business Intelligence Engineer to lead our analytics and measurement strategy during a crucial phase of product expansion in the EU. Our team is embarking on several strategic product launches across European markets, and requires a seasoned analytics leader to build and own comprehensive measurement and reporting capabilities that will shape these products' success.

We are seeking a candidate with a strong background in quantitative analysis, data science, econometrics, or applied statistics who can dive deep into complex business problems. This role will drive a wide range of diagnostic and descriptive analytics through data exploration, hypothesis testing, correlation analysis, and analytics engineering to meet the reporting and business analysis requirements of both AVS and VX programs. The successful candidate will be instrumental in designing and implementing measurement frameworks for our new product launches, ensuring we capture meaningful insights across various business metrics and program KPIs.

We are particularly interested in hearing from candidates who have experience in product analytics or data/statistical analysis for product enablement and experimentation. A successful candidate will be able to partner effectively with both business and technical teams, demonstrating clear communication of results and the ability to influence a variety of stakeholders, from product managers to senior leadership.

Responsibilities
  • Create the right datasets needed for the setup and launch of new products
  • Design and track metrics to measure the business impact of product launches
  • Conduct deep dives into program metrics and data to identify root causes and drivers
  • Identify new data sources and metrics and create plans to harvest this data
  • Build tools and automated reporting capabilities needed to serve the reporting requirements for both AVS and VX
  • Support functional teams on ad hoc data requests and address their analytical needs
  • Partner with other data teams members (scientists and data engineers) at delivering data products that range from analytical reports to complex science models
About the team

The AVS and VX program teams are diverse organizations with employees across Europe and with partner teams around the globe. This role can be based in London, Paris, Madrid, Munich, Berlin, Milan or Luxembourg. These teams drive improvements in products, services, tools, processes, communication, and vendor education world-wide working with partner teams in Europe, North America, Japan, and emerging locales and are responsible for all elements of a vendor's interaction with Amazon including listing, catalog management, ordering, supply chain, marketing, payments, value-added services, and vendor support.

Experience and skills
  • 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
  • Knowledge of data warehousing and data modeling
Locations

This position is open to the following locations: London, Luxembourg, Paris, Madrid, Milan, and Berlin.

Company and equal opportunity statement

Amazon strives to be Earth's most customer-centric company, where customers can find and discover anything they might want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience - Amazon continues to grow and evolve as a world-class e-commerce website. Core to Amazon's mission to delight and serve customers is a need to invent on behalf of vendors. Our team is at the forefront of two pivotal programs, EU AVS and WW VX, each integral to enhancing the end Customer Experience and contributing to Amazon's Long-Term Free Cash Flow. The EU AVS program aims to provide an industry-leading account management service at the optimal cost-to-serve for Amazon that exceeds vendors' expectations and expedites their growth on Amazon. The WW VX program vision is to make Amazon the most preferred, trusted, and efficient distribution option for vendors by building an industry-leading experience for every vendor across all global touchpoints.

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.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Business Intelligence Engineer, DNA

Senior Business Intelligence Engineer, DNA

Senior Engineer - Business Intelligence

Senior Engineer - Business Intelligence

Senior Business Intelligence Analyst - Product and Supplier Management

Senior Business Intelligence Analyst - Product and Supplier Management

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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.