Business Data Technologies (BDT) makes it easier for teams across Amazon to produce, store, catalog, secure, move, and analyze data at massive scale. Our managed solutions combine standard AWS tooling, open-source products, and custom services to free teams from worrying about the complexities of operating at Amazon scale. This lets BDT customers move beyond the engineering and operational burden associated with managing and scaling platforms, and instead focus on scaling the value they can glean from their data, both for their customers and their teams.
We own the one of the biggest (largest) data lakes for Amazon where 1000’s of Amazon teams can search, share, and store EB (Exabytes) of data in a secure and seamless way; using our solutions, teams around the world can schedule/process millions of workloads on a daily basis. We provide enterprise solutions that focus on compliance, security, integrity, and cost efficiency of operating and managing EBs of Amazon data.
Key job responsibilities
As a Software Development Engineer, you will:
Lead architecture of large initiatives in scaling, security and availability.
Design, develop and support a world-class system that serves diverse user profiles and teams
Produce bullet-proof code that is robust, efficient and maintainable; our primary languages are Java and Python
Continually challenge what exists and explore what should be changed to best meet evolving business and market needs.
Possess expert knowledge in large scale distributed system design and engineering best practices
Participate in setting a vision and objectives in alignment with business and market needs
Drive and work on algorithm and architecture design, execute and deliver results.
Invent the future, instead of just being a bystander
Join a great group of motivated, top-notch, people and work with them to solve interesting and useful problems in a fun, collaborative environment
About the team
BDT Data Quality team strives to simplify the experience of dataset owners and consumers to deeply understand the quality of data they produce and consume, enabling them to keep the quality of their data high, and to quickly understand the content and structure of their data, identify when it varies, and by how much. We do so by providing cost effective automation of data quality statistics and exposing those statistics in easily consumable user experiences, so that consumers may easily discover the data that works best for them without having to perform their own data analysis, and producers can measure, report, and alarm on variances in produced data to keep data quality high.