The Neuron team, part of Business Data Technologies (BDT), builds services that drive cost efficiency and fiscal responsibility across Amazon. Our charter consists of internal chargeback billing, resource efficiency and cool visualizations that marry machine learning-backed recommendation systems with large datasets. Our customers use our services to identify and eliminate wasteful use of AWS technologies and to drive charge-back billing for eCF Data foundational services, including BDT's data lake Andes.
We are looking for software developers who long for the opportunity to design and build large-scale systems for analyzing and deriving insights from data. More specifically, we need your help to build systems that analyses data and potentially machine learning to automate cost attribution of $80MM+ in annual infrastructure spend. You will improve user productivity and service resiliency by enabling recommendation systems that optimizes Amazon's use of infrastructure for storage and analytics.
What does it take to succeed in this role? You need to be creative, responsible, and excited to dig deep into AWS technologies. You will think about business opportunities, operational issues, architectural improvements, and the customer perspective in the source of a single conversation. You will learn to master programming languages, distributed system design, and performance, and if you are curious, learn to harness the capabilities of Machine Learning.
Key job responsibilities
Your responsibilities will include:
- 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
- Work across teams to drive deliver features critical to our overall strategy
- Working with AWS technologies like Athena, Batch, DynamoDB, Lambda, Redshift, S3, SageMaker, Step Functions, and more.
A day in the life
As an engineer on the Neuron team, you'll be using AWS (not MAWS) to build software using CDK, Java, Spark and Scala, and various web technologies. You'll engage with AWS to innovate within your space and try out new technologies to simplify the way we process data and generate insights, and perhaps most importantly, streamline our operational preparedness (the operational load is low as we invest in refactoring.) You'll connect with stakeholders and internal customers to learn about their needs, and design technical solutions to deliver results. With a focus on fun, we have weekly socials and knowledge sharing meetings!
About the team
The Neuron team consists of backend, frontend and machine learning engineers, as well as project and product managers. Our culture is built around recognising diverse perspectives and we do not suppress opinions for the sake of conformity. In the same vein, we work together and empower one another to grow our careers. The goal is learn and have fun together while delivering results for Amazon!
We always strive to use AWS serverless technologies, and processes that can be safely automated, we automate. We also recognise that all software eventually runs its course, always looking to deprecate undifferentiated technologies.
There is an option to work remote from across Canada for successful candidates.BASIC QUALIFICATIONS
- Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
- 1+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
- 2+ years of non-internship professional software development experience
- Experience with AWS data stores and data ETL technologies.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.
Software and Programming