Amazon

Business Intelligence Engineer, Amazon Grocery Data and Tech

Posted On

Feb. 4, 2025

Location

Bengaluru, Karnataka

Experience Level

Freshers/Experienced

Job Type

Project/Program/Product Management--Technical

Apply By

Feb. 25, 2025

Job Description

At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. We are looking for a Business Intelligence Engineer in the Amazon Grocery Data and Tech.

As a Business Intelligence Engineer, you will be responsible for execution of rapidly evolving complex demands, design, development, testing, deployment and operations of multiple analytical solutions. You will be responsible for delivering some of our most strategic analytics initiatives. You will create insights that support all of Amazon’s grocery businesses and have a significant impact on Amazon’s top-line and competitive position.

A successful candidate will bring deep technical expertise, strong business acumen and judgment, ability to define ground breaking products, desire to have an industry wide impact and ability to work within a fast-moving environment in a large company to rapidly deliver services that have a broad business impact. They will define metrics to measure business performance and drive efficiency improvements.

About the team
Amazon Grocery Data and Technology (GDT) team is the central data team for Amazon Grocery, consisting of engineering teams (BIEs/DEs/SDEs). We are the direct owner of (a) Infrastructure and services used for reading, processing, reporting and enrichment of grocery data; (b) Productivity tools; (c) Reporting solutions for worldwide 1P and 3P customers across the following businesses: Amazon Fresh Grocery (AFG), Whole Foods Market (WFM), Amazon Go, Amazon Grocery Partners, etc. - 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
- Experience with scripting language (e.g., Python, Java, or R)

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