As a Business Intelligence Engineer within the Placement team, you will play a crucial role as a member of a high-performance and fungible Business Intelligence team. Your responsibilities include conducting end-to-end analytics at the intersection of various advanced Amazon systems, getting global visibility of how Amazon functions and serves our customers. Your curious mind will dive deep into complex systems, and create analytical tools that drive ever-greater scalability and optimization of every aspect of placement, removing cost and delivering speed of execution to thrill our customers. The impact of your work will be global, material and remarkable.

Key job responsibilities
Major responsibilities include:
• Design / Build / Scale
a. Gather requirements from internal or external customers and work backwards those to design analytical solutions to solve business needs.
b. Create end-to-end analytical solutions (i.e. Datasets, data pipelines, dashboards, predictive models, process automation, etc.) which scale worldwide using technologies such as Redshift, Datanet, Quicksight, Cradle, Python, etc.
c. Contribute to and follow best practices for development of analytical solutions components including query optimization, table design and data visualization.
• Deep Dive into Systems
Understand the functioning of Placement systems and their upstream and downstream interactions with other SCOT systems in order to produce better and faster analytical products.

• Measure / Quantify / Expand
a. Translate business questions and concerns into specific quantitative questions that can be answered with available data using sound methodologies. In cases where questions cannot be answered with available data, work with engineers to produce the required data.
b. Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.
c. Explore/analyze data and work with Research Scientists, Data Scientists and Product Managers to understand system behaviors, spot defects, and benchmark our ability to serve our customers
d. Given anecdotes about anomalies, design strategies to quantify the overall impact of such anomalies, deep dive to explain why they happen, and identify fixes.
• Mentoring / Learning
a. Coach junior members of the team and/or other external teams about how Placement systems works and best practices for data analytics.
b. Engage proactively in continuous learning initiatives to consistently enhance and broaden your toolkit of supply chain systems and data technologies.

About the team
The Inventory Placement team within the Supply Chain Optimization Technologies organization seeks a Senior Business Intelligence Engineer to help evolve state-of-the-art algorithms that determine where each unit entering the Amazon Fulfillment Network worldwide should be placed to maximize shipping speed and minimize cost.