Business Intelligence Engineer, AWS Infrastructure Services (AIS)

Amazon
London
1 month ago
Applications closed

Related Jobs

View all jobs

Data Engineering Lead

Data Engineering Lead

Data Engineering Lead / Data Architect

Senior Data Engineer

MLOps & AI Engineer Lead

Machine Learning Specialist

Business Intelligence Engineer, AWS Infrastructure Services (AIS)

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain and we’re looking for talented people who want to help.

You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

Do you love problem solving? Are you looking for real world Supply Chain challenges? Do you have a desire to make a major contribution to the future, in the rapid growth environment of Cloud Computing?

Amazon Web Services is looking for a highly motivated, analytical and detail oriented candidate to help build scalable, predictive and prescriptive business analytics solutions that supports AWS Supply Chain and Procurement organization. You will be part of the Supply Chain Analytics team working with Global Stakeholders, Data Engineers and Business Analysts to achieve our goals.

The successful candidate will be a self-starter with a combination of superior analytical and technical abilities, business acumen, and written and verbal communication skills. Data-driven decision-making is at the core of Amazon’s culture. The ideal candidate has deep expertise in gathering requirements and insights, mining large and diverse data sets, data visualization, writing complex SQL queries, building rapid prototypes using Python/R, and generating insights that enable senior leaders to make critical business decisions. The ideal candidate has experience providing guidance and support for other engineers with industry best practices and direction. They are comfortable with ambiguity and communicate clearly and effectively to all levels of the company, both in writing and in meetings. They are motivated to achieve results in a fast-paced environment.

Key job responsibilities

  1. Understand a broad range of Amazon’s data resources and processes.
  2. Interface with Global Stakeholders, Data Engineers, and Business Analysts across time zones to gather requirements by asking right questions, analyzing data, and drawing conclusions by making and validating appropriate assumptions.
  3. Conduct deep dive analyses of business problems and formulate conclusions and recommendations; determine optimized courses of action to deliver comprehensive Analytical solutions.
  4. Enhance analytical maturity through predictive and prescriptive analytics using Machine Learning and Optimization techniques.
  5. Produce written recommendations and insights for key stakeholders to help shape solution design.
  6. Design, develop and maintain scalable and reliable analytical tools, dashboards, and metrics that drive key supply chain and procurement decisions.
  7. Handle multiple projects at once, deal with ambiguity and rapidly-changing priorities.

BASIC QUALIFICATIONS

  • Bachelor’s degree in Engineering, Statistics, Computer Science, Mathematics, Economics, Data Science or related field.
  • 6+ years’ hands-on analytics work experience, with proven quantitative orientation.
  • 3+ years’ experience using business intelligence tools like Tableau, QuickSight, PowerBI etc. Hands-on experience in Python, SQL, Data Warehouse solutions and databases.
  • Experience building measures and metrics, and developing reporting solutions.
  • Ability to think big, understand business strategy, provide consultative business analysis, and leverage technical skills to create insightful BI solutions.

PREFERRED QUALIFICATIONS

  • Master’s degree in Data Science, Operations, Statistics from a premium institute, or MBA from premier business schools.
  • 4+ years’ experience in Supply Chain Analytics, Data Science or related specialty.
  • Experience with AWS technologies like Redshift, S3, Lambda, Glue.
  • Experience in statistical computing using Python/R.

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

Amazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.