Business Intelligence Engineer, Core Shopping Analytics

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Job Description - Business Intelligence Engineer, Core Shopping Analytics

DESCRIPTION

Core Shopping (CS) Analytics turns disparate, raw data into actionable insights that improve every customer’s ability to securely discover, evaluate, and purchase products and services across the Amazon store. We own the analytics for the Navigation, Homepage, Inspire, App First, Detail Page, Cart, Checkout, Add-to-Cart, and Address experiences. Key job responsibilities
You are the Analytics subject matter expert on the App-First & List team, trailblazing to experiment what great app-first experiences can look like for Amazon shopping apps and helping customers utilize the List functionality to improve their shopping experience. You will own the core datasets to understand how customers use the Navigation features. Collaborating with Product Managers and Engineers, you will develop a framework to understand the levers that drive a better experience. You will deliver in-depth analysis and recommendations to drive the product roadmap, generating incremental business value. As the chief evangelist, you will drive adoption of your dataset and mental model across the Consumer organization. Lastly, you will collaborate with a 10+ team of BIEs, DEs and DSs to understand how App-first and Lists fits into the broader shopping journey to improve the end-to-end shopping experience. A day in the life
We build in 5-week Sprints with 1 week for planning and 4 weeks for execution. Planning Week is used to groom the backlog and to scope & prioritize projects. We reserve the Friday of every Planning Week for a self-directed Learning Day. Over the 4 Execution Weeks, we have regular stand-ups and a mid-sprint demo. Projects will vary sprint to sprint among building derived/aggregate datasets, conducting analysis, and pushing learnings to customers. About the team
Today, we empower 500+ Builders directly and 100+ unique partner teams via our ‘Source of Truth’ datasets, self-service dashboards/gits, scheduled reports, and custom metrics consumed for cross-store evaluation. In 2023, we supported new experiences end-to-end from logging to reporting/self-service and continued maturing our foundational service offerings to enable more bandwidth for insight generation. We are open to hiring candidates to work out of one of the following locations: Vancouver, BC, CAN

BASIC QUALIFICATIONS

- 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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