Are you interested in diving deep into the data and engineering the metrics model that drives continuous improvement for Amazon’s eCommerce systems? Do you have solid problem-solving abilities, metrics-driven decision making and want to solve problems with solutions that will meet the growing worldwide need for Amazon’s products? Then eCommerce Services is the team for you. We are part of building the world's best, most reliable, and most feature-rich eCommerce platform that provides customers the best experience possible and are looking for a top-notch Senior Business Intelligence Engineer.In eCommerce Services (eCS), we build systems that span the full range of eCommerce functionality, from Privacy, Identity, Purchase Experience and Ordering to Shipping, Tax and Financial integration. eCommerce Services manages several aspects of the customer life cycle, starting from account creation and sign in, to placing items in the shopping cart, proceeding through checkout, order processing, managing order history and post-fulfillment actions such as refunds and tax invoices. eCS services determine sales tax and shipping charges, and we ensure the privacy of our customers. Our mission is to provide a commerce foundation that accelerates business innovation and delivers a secure, available, performant, and reliable shopping experience to Amazon’s customers.We are looking for an experienced and technically skilled individual to join our Data Engineering and Analytics team as a Sr. Business Intelligence Engineer (BIE). The ideal candidate will be an analytical, results-oriented, self-motivated, and customer-focused Business Intelligence Engineer who will play a key role in continuous improvement for the critical systems that enable our entire retail business. The role will also include surfacing key product metrics as well as building critical data pipelines and analytics tools to improve efficiency and quality of strategic business decisions.Key job responsibilities• Defining, developing and maintaining critical business and operational metrics reviewed on a weekly, monthly, quarterly, and annual basis.• Analysis of historical data to identify trends and support decision making, including written and verbal presentation of results and recommendations.• Collaborating with software development teams to implement analytics systems and data structures to support large-scale data analysis and delivery of reports.• Identifying data needs and driving data quality improvement projects.• Thought leadership on data mining and analysis. Understanding the broad range of Amazon’s data resources, which to use, how, and when. Mining and manipulating data from database tables, simulation results, and log files.