Amazon Business Intelligence Engineer Amazon Private Brands 

United States, Washington, Seattle 

426914996

In this role, you'll be a key connector between the various facets of Amazon Private Brand data, driving insights across areas like sustainability, compliance, sourcing, and more. To succeed you'll need excellent SQL and Git skills as well as ETL optimization experience and visualization tool expertise. Most importantly you need to be a strong communicator who is able to prioritize and make tradeoffs quickly.Key job responsibilities
As a business intelligence (BI) engineer within Amazon Private Brands, you will be a crucial member of our data analytics team, responsible for designing, implementing, and maintaining robust BI solutions that empower our business stakeholders to make data-driven decisions. Your key responsibilities will include collaborating closely with the business and subject matter experts to deeply understand their reporting and analytics requirements.Leveraging your expertise, you will design and develop complex data models, ETL (extract, transform, load) processes, and interactive dashboards/visualizations using AWS services like Redshift, Glue, Amazon Quicksight, and LLMs like Amazon Q. Automating data integration and transformation workflows will be a core part of your role, ensuring timely, accurate, and scalable reporting capabilities.Additionally, you will be responsible for optimizing query performance to support increasing data volumes and user demands, guaranteeing our BI infrastructure remains efficient and reliable. Providing data support and hands-on training to end-users will also be a key focus, as will continuously staying on top of the latest BI trends and technologies to recommend strategic improvements.A day in the life

- 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 using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling