Description We are seeking a Business Intelligence Engineer to drive the development of data engineering infrastructure and solutions that can scale across Amazon's largest vendors. In this role, your primary focus will be on designing and building robust data pipelines, architectures, and platforms to support the delivery of advanced analytics and machine learning models for our eCommerce partners as a part of Amazon's new generation of Paid Services. You will work directly with our product managers to prototype analytical and BI solutions and scale to hundreds of vendors, and even change the market, both in JP and WW, and with other business intelligence engineers and data engineers to develop the infrastructure necessary to deploy productionized solutions through code. As a member of the team you will also work with vendors, team members, and internal and external partners to give input into the way we work, how we serve customers, and where we invest in future capabilities. This position is ideal for candidates with a strong background in data engineering, a passion for building scalable and efficient data solutions, and a desire to drive tangible business impact through data-driven insights. You will have the opportunity to work on challenging projects that push the boundaries of what is possible, while contributing to the success of Amazon's largest vendor partnerships. Key job responsibilities The BIE is accountable for: (1) Defining together with PMs requirements and design for a scalable deployment of solutions through paid services, leveraging tools on AWS and CDK (2) Identify appropriate metrics and feature sets for the problem, and build/maintain automated pipelines for their extraction. (3) Utilizing Amazon systems and tools to effectively work with terabytes of data. (4) Independently apply models developed by science team to vendor use cases and draw business conclusions from results. (5) Actively contribute to and maintain internal team BI infrastructure and solutions. (6) Prepare materials for vendor facing presentations and distil vendor problems into technical requirements. About the team In this position, you will be part of the JP Science and Data team, consisting of scientists, business intelligence engineers, data engineers, and machine learning engineers, collaborating with Product Managers and Software Developers worldwide. Our current projects touch on the areas of causal inference, representation learning, anomaly detection, forecasting, LLMs and more. As part of working on Paid Services, you will be exposed to all other projects the team works on: we believe that collaboration is paramount, and working in isolation does not lead to a happy team. We place strong emphasis on continuous learning through internal mechanisms for our team members to keep on growing their expertise and keep up with the state of the art. Our goal is to be primary science team for vendor solutions in Amazon, worldwide. Basic Qualifications - 2+ 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 in Statistical Analysis packages such as R, SAS and Matlab - Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling Preferred Qualifications - Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift - Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.