Business Intelligence Engineer Intern, Amazon

• Experience in analyzing and interpreting data with Redshift, Oracle, NoSQL etc
• Experience with data visualization using Tableau, Quicksight, or similar tools
• Experience with data modeling, warehousing and building ETL pipelines
• Experience in Statistical Analysis packages such as R, SAS and Matlab
• Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
• Experience with SQL
• Experience in the data/BI space
• 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

Desirable

• 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
• How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow
• At Amazon, we hire the best minds in technology to innovate on behalf of our customers
• The 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
• 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
• 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 analyze data
• Analyze 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