Business Intelligence Engineer Amazon
Seattle, WA

Job Description

Amazon aims to exceed the expectations of our customers by ensuring that their orders, no matter how large or small, are delivered as quickly, accurately, and cost effectively as possible. To meet this goal, Amazon has invested in Amazon F3 Retail, a world class customer-centric operation. We are looking for a dynamic, resourceful, and organized engineer within Amazon F3PO organization to develop new, data-driven solutions to support the most critical components of this rapidly scaling operation.

Amazon F3PO Science team has an opening for an engineer. The candidate will have an opportunity to collaborate with a team of economists, research scientists, and software development engineers in developing the best in class solutions to help optimally serve customers and manage F3 ultra-fast grocery delivery operations. The team owns fulfillment, delivery optimization and post-order customer experience for all grocery delivery from Whole Foods, Amazon Fresh, Prime Now, and 3P stores. By partnering with more than 5 Tech teams across F3, GSF, and Last Mile, we develop measurement, forecasting and optimization models in order to build tech integrated automated and scalable solutions. Ultra-fast grocery delivery requires us to build science-tech solutions which are dynamic and real-time. The current portfolio of projects include an automated experimental platform to measure customer preferences (tradeoffs between delivery time and delivery price), real-time demand forecast (with 5-min real time update), real-time out-of-stock prediction, and online automated labor capacity planning and management system for Whole Foods stores and Prime Now FCs.

As an Engineer, you should be an expert in the architecture of DW solutions for the Enterprise using multiple platforms. You should excel in the design, creation, management, and business use of extremely large datasets. You should have excellent business and communication skills to be able to work with scientists and engineers to determine how best to design the data warehouse for data science modeling and analytics. You will be responsible for designing and implementing scalable ETL processes in the data warehouse platform to support the rapidly growing and dynamic business and science demand for data, and use it to deliver the data as service which will have an immediate influence on day-to-day decision making. You should have the ability to develop and tune SQL to provide optimized solutions to the business. The required engineer will also support computational infrastructure for science modelling and model automation prototypes. You will design the optimal computational architecture such computational servers (dev-desktop, EC2 and EMR) and storage clusters (S3, DynamoDB and redshift).