As a Business Intelligence Engineer II on the Amazon Worldwide Grocery team, you will support analytics and metrics dashboards for in-store products including Amazon Dash Carts, Point of Sale, Self Checkout, Digital Displays, and more. You will partner with product management teams to drive key business decisions, monitor service health, and measure customer engagement through data-driven insights.
Key job responsibilities
Design, develop, and maintain analytics dashboards and reporting solutions that provide actionable insights for in-store product performance
- Partner with product managers to define key metrics and success criteria for Amazon Grocery in-store technologies
- Build and optimize data pipelines to ensure accurate and timely data collection from multiple sources
- Analyze complex datasets to identify trends, anomalies, and opportunities for product improvement
- Create visualizations that effectively communicate insights to technical and non-technical stakeholders
- Monitor service health metrics and develop alerting mechanisms for critical KPIs
- Support A/B testing initiatives to measure the impact of product changes on customer engagement
- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions
About the team
The Grocery Retail and In-Store Experience team owns the products that power checkout and in-store customer engagement, helping shopper save time and money, and enabling store associates to do their jobs more effectively. Products include Dash Cart, Self-Checkout (SCO), Point of Sale (POS), Electronic Shelf Labels, Digital Displays, In-Store Mode for the Amazon app, and more.- 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- 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
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