Business Intelligence Engineer Intern - UK
Amazon
London, GB
3d ago

Do you enjoy solving complex problems and troubleshooting products? Are you passionate about developing test strategies, finding, and tracking bugs to resolution, and innovating on behalf of customers?

Do you want to be a part of a fast-paced, ambiguous environment and contribute to one of the most visited sites on the Internet?

At Amazon, we hire the best minds in technology to innovate on behalf of our customers. The intense focus we have on our customers is why we are one of the world’s most beloved brands customer obsession is part of our company DNA.

Business intelligence engineers use cutting-edge technology to solve complex problems and get to see the impact of their work first-hand.

The challenges business intelligence engineers solve for at Amazon are big and affect millions of customers, sellers, and products around the world.

Our path is not always simple, so we are selective about who joins us on this journey. There is a certain kind of person who takes on this role at Amazon someone who is excited by the idea of creating new products, features, and services from scratch while managing ambiguity and the pace of a company whose ship cycles are measured in weeks, not years.

The Amazon EU Student Programs Team are looking for ambitious students to join us as interns at the heart of our core consumer business! Internships are flexible in length to fit in with your university’s placement scheme.

Come chart your own path at Amazon.

Responsibilities :

As a business intelligence engineer, you will / may :

  • Develop analytical solutions to business problems that utilize the highest standards of analytical rigor and data integrity
  • Recognize and adopt best practices in reporting and analysis : data integrity, test design, analysis, validation, and documentation
  • Write high quality code to retrieve and analyse data
  • Analyse and solve business problems at their root, stepping back to understand the broader context
  • Design pragmatic analyses and automated metrics that add value to your business area
  • Understand data resources and how, when, and what to use (and what not to use).
  • Develop analyses (whether fully formed or exploratory) for the business’ sake, not for analyses’ sake
  • Seek to understand the business objectives relevant to your area, and align your work to those objectives and seek to deliver business value
  • Proactively and continually, improve your level of knowledge about Amazon’s business and relevant data resources
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