Business Intelligence Engineer, Core Shopping Analytics

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 Homepage, Navigation, Reviews, Detail Page, List, App First, and Cross-Store experiences.

Key job responsibilities

You are an Analytics subject matter expert, helping customers discover, find, and evaluate items across the Store. You will own the core datasets to understand how customers use your experience's 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 your experience 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 2026, we will support 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.

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

PREFERRED QUALIFICATIONS

• Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
• Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information.

If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location.

Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Seattle - 99,500.00 - 160,000.00 USD annually