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Business Intelligence Engineer, Amazon Grocery Data and Tech
Last Date to Apply: Feb. 25, 2025
ApplyAdded Today : 38
Expired Today : 137
Amazon
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. - 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 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
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