Data Engineer II, Business Data Technologies

Amazon’s eCommerce Foundation (eCF) organization is responsible for the core components that drive the Amazon website and customer experience. Serving millions of customer page views and orders per day, eCF builds for scale.
As an organization within eCF, the Business Data Technologies (BDT) group is no exception. We collect petabytes of data from thousands of data sources inside and outside Amazon including the Amazon catalog system, inventory system, customer order system, page views on the website and Alexa systems. We also support Amazon subsidiaries such as IMDB and Audible. We provide interfaces for our internal customers to access and query the data hundreds of thousands of times per day, using Amazon Web Service’s (AWS) Redshift, Hive, and Spark. We build scalable solutions that grow with the Amazon business.

Key job responsibilities
As an Amazon.com Data Engineer II you will be working in one of the world's largest cloud-based data lakes. You should be skilled in the architecture of data warehouse solutions for the Enterprise using multiple platforms (EMR, RDBMS, Columnar, Cloud). You should have extensive experience in the design, creation, management, and business use of extremely large datasets. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and to build data sets that answer those questions. Above all you should be passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions and drive change.

As a Data Engineer II on Amazon.com’s Business Data Technologies team, design, develop, implement, test, and operate large-scale, high-volume, high-performance data structures for analytics and deep learning. Implement data ingestion routines both real time and batch using best practices in data modeling, ETL/ELT processes leveraging AWS technologies and Big data tools. Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions that work well within the overall data architecture. Analyze source data systems and drive best practices in source teams. Participate in the full development life cycle, end-to-end, from design, implementation and testing, to documentation, delivery, support, and maintenance. Produce comprehensive, usable dataset documentation and metadata. Evaluate and make decisions around dataset implementations designed and proposed by peer data engineers. Evaluate and make decisions around the use of new or existing software products and tools. Mentor junior data engineers.


About the team
At BDT, We collect petabytes of data from thousands of data sources inside and outside Amazon including the Amazon catalog system, inventory system, customer order system, page views on the website and Alexa systems. We also support Amazon subsidiaries such as IMDB and Audible. We provide interfaces for our internal customers to access and query the data hundreds of thousands of times per day, using Amazon Web Service’s (AWS) Redshift, Hive, and Spark. We build scalable solutions that grow with the Amazon business.