Business Intelligence Engineer Amazon
Seattle, WA

Job Description

Global Specialty Fulfillment (GSF) comprises of Prime Now, Fresh, Ultra-Fast Fresh (UFF) offering, Restaurants and Whole Foods (WFM) operations. The Delivery Operations Excellence team is responsible for the Delivery Cost and Quality metrics for these businesses which entails leading the Trans WBRs. The team is building new operational data models and metrics that will fundamentally change the way GSF surfaces and appraises quality, cost, and capacity variation: we will surface outliers in root cause activities and tool settings and strive to early detection. This endeavor will allow us to recommend adjustments of operational levers to upstream partner teams in order to maintain customer experience.

The Delivery Operations Excellence team is seeking a Business Intelligence Engineer (BIE) to help define and create the next generation of deep dive and performance metrics visibility tools. Our ideal candidate thrives in a fast-paced environment, enjoys the challenge of highly complex business scenarios, can synthesize customer requirements in order to define analytical products, and is passionate about data and analytics. To be successful in this role you will need to have superior analytical, communication, presentation, and organizational skills.

Responsibilities Include:

* Propose and implement new business metrics for senior management reviews; identify data sources, design and develop data infrastructure to support these metrics for business growth.
* Design and develop highly available dashboards and metrics using appropriate software and programming solutions
* Partner with other analysts and engineers to build analytical solutions to deliver on business goals
* Enable effective decision making by retrieving and aggregating data from multiple sources and compiling it into a digestible and actionable format
* Perform analysis of historical data to identify contributing factors to the output metrics, model the relationships and predict the impact of variations with high confidence