Data Engineer, JP Science and Data

Amazon's JP Science and Data team is seeking a Data Engineer to drive the development of data engineering infrastructure and solutions that scale across Amazon's largest vendors. This role focuses on designing and building robust data pipelines, architectures, and platforms to support advanced analytics and machine learning models for eCommerce partners as part of Amazon's new generation of Paid Services.

The position offers an opportunity to work with a diverse team of scientists, business intelligence engineers, data engineers, and machine learning engineers, collaborating on cutting-edge projects in causal inference, representation learning, anomaly detection, forecasting, and LLMs. The team aims to be the primary science team for vendor solutions in Amazon worldwide.

As a Data Engineer, you'll work directly with other engineers and product managers to design and implement scalable data infrastructure supporting BI solutions for hundreds of vendors. You'll have the chance to influence the team's working methods, customer service approach, and future capability investments.

The role requires expertise in data engineering, particularly in AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, and Lambda. You'll be working in an inclusive culture that emphasizes continuous learning and collaboration, with exposure to various projects across the team.

This is an excellent opportunity for someone passionate about building scalable data solutions and driving business impact through data-driven insights, while working on challenging projects that push technological boundaries and contribute to Amazon's largest vendor partnerships.