Description

Amazon Lab126 is an inventive research and development company that designs and engineers high-profile consumer electronics. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc., originally creating the best-selling Kindle family of products. Since then, we have produced devices like Fire tablets, Fire TV, Amazon Echo and Amazon Show. The Amazon Devices group delivers delightfully unique Amazon experiences, giving customers instant access to everything, digital or physical.

We are seeking an exemplary Data Engineer with broad technical skills to develop, own, and support the underlying data infrastructure and data pipelines that fuels our business analytics and research. The ideal candidate demonstrates thought leadership in data engineering practices and possesses a strategic vision for building scalable products and solutions. We look for candidates who are excellent communicators and have demonstrated leadership experience.

This role has great exposure to a broad scope that can really help shape the future of Global Operations products. The successful candidate will have a proven track record of leading and implementing strategies that align with organizational goals and demonstrate the ability to influence and guide technical decisions at a strategic level. You will have excellent problem solving abilities, and the ability to synthesize data into crisp and clear recommendations for our customers. You will have broad skills in data infrastructure management, database design, be comfortable dealing with ambiguity, large and complex data sets, develop complex data pipelines, and experience with CI/CD.

Key job responsibilities
· Design, implement, and support a platform providing ad-hoc access to large datasets
· Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL
· Build robust and scalable data integration (ETL) pipelines using SQL, Python and AWS services such as Data Pipelines, Glue
· Implement data structures using best practices in data modeling, ETL/ELT processes, and SQL/Redshift
· Interface with business customers, gathering requirements and delivering complete reporting solutions
· Build and deliver high quality datasets to support business analyst and customer reporting needs
· Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers