The Business Data Technologies (BDT) group at Amazon is hiring in New York City to create the next generation analytic stack for organizing, managing, and processing extremely large scale data. Join us to create the future of big data processing and analytics solutions for one of largest and most complex data lakes in the world.
BDT is growing, and the data processing landscape is shifting. Our data is consumed by thousands of teams across Amazon including Research Scientists, Machine Learning Specialists, Business Analysts and Data Engineers. BDT is building an enterprise-wide Data Marketplace leveraging AWS technologies. We enable teams at Amazon to produce analytical data in any form of storage (S3, DynamoDB, Aurora, etc.) and process that data using any type of compute environment such as EMR/Spark, Redshift, Athena, and others via a common execution bus. We are developing innovative products including the next-generation of data lake, data discovery engine, data transformation platform, data quality and visualization services.
This is a hands-on position where you will do everything, starting from our customer, solving the toughest problems to delight them and provide the best experience. You will drive technical strategy and direction, design and build massively scalable components, mentor junior engineers and collaborate with our partner organizations. To succeed in this role you need to be customer obsessed, drive results and have a real passion for data, analytics and computing at scale.
Your responsibilities will include:
* Working backwards from the customer translation complex functional and technical requirements into detailed architecture and design. * Deliver systems and features on schedule with high quality * Stay current on technical knowledge to keep pace with rapidly changing technology, and work with the team in bringing new technologies on board * Mentor of junior engineers * Work across teams to drive overall technical strategy
To get a better idea on the work we have done read the following use case stories: