AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help.

You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

We are looking for a talented Data Engineer to join the Manufacturing Operations, Transportation Operations, and Reverse (MOTOR) organization in support of our Supply Chain Intelligence team. MOTOR manages the manufacturing of datacenter racks and the movement of racks/parts through the supply chain, consisting of transportation, warehousing, and reverse logistics into and out of the data centers. This role performs helps connect the different systems across the supply chain together so operational teams have clean, actionable data to work with. This requires someone with strong analytic skills and business acumen who can work with stakeholders on strategic projects across MOTOR.

The ideal candidate relishes working with large volumes of data, enjoys the challenge of highly complex technical contexts, and, above all else, is passionate about data and analytics. Must be an expert working with data modeling with un/structured data, ingestion pipelines and ETL design and business intelligence tools with the business to identify strategic opportunities where improvements in data infrastructure creates out-sized business impact. Candidate is a self-starter, comfortable with ambiguity, able to think big (while paying careful attention to detail), mentors other engineers in team on high quality tech, and enjoys working in a fast-paced team. Candidate will have a chance to architect the data pipelines needed for optimization and predictive analysis. We're excited to talk to those up to the challenge!



Key job responsibilities
- Build and maintain the infrastructure to answer questions with data, using software engineering best practices, data management fundamentals, data storage principles, recent advances in distributed systems, and operational excellence best practices. Build datasets that analysts and scientists use to generate actionable insights.
- Define the data engineering processes that leverage various AWS services to improve accessibility, redundancy, data integrity, cost, and storage requirements.
- Develop high quality solutions for the faster development of the products/models that solve the business needs in a scalable format, while also anticipating future requirements.
- Collaborate with Research/Applied Scientists, Data Engineers, Business Intelligence Engineers, Data Scientists, Business Analysts, and Product/Program Managers to understand the business and technical requirements, and make decisions that help make the products/programs smoother.
- Interface with other technology/data engineering teams to extract, transform, and load data from a wide variety of data sources using and AWS data technologies.
- Lead the technical design and implementation of the data infrastructure.
- Design and manage data audit, quality, and reconciliation processes in collaboration with various stakeholders.



About the team
This team provides data engineering and business intelligence engineering services to the rest of MOTOR. We are the data experts behind the scenes helping the operational teams focus on operations by ensuring they have accurate, timely data and provide business insights to help improve operational excellence.