Amazon has come a long way since opening on the World Wide Web in July 1995. Today, we operate retail websites in multiple countries across geographies, offering products in many categories (books, media, digital, electronics etc.) worldwide, and we still like to work hard, have fun and make history! The Amazon.com brand has become synonymous with a superior level of convenience, selection, low prices, and customer service. We have over 130 million active customers as of 2010.
As a Data Engineer, you are responsible for analyzing large amounts of business data, solving real world problems, and developing metrics and business cases that will enable us to continually delight our customers worldwide. You will work with a team of Product Managers, Software Engineers, Scientists and Business Intelligence Engineers to automate and scale the analysis, and to make the data more actionable to manage business at scale. You will own many large datasets, implement new data pipelines that feed into or from critical data systems at Amazon.
Key job responsibilities
1. Responsible for designing, building and maintaining complex data solutions for Amazon's Operations businesses
2. Actively participates in the code review process, design discussions, team planning, operational excellence, and constructively identifies problems and proposes solutions
3. Makes appropriate trade-offs, re-use where possible, and is judicious about introducing dependencies
4. Makes efficient use of resources (e.g., system hardware, data storage, query optimization, AWS infrastructure etc.)
5. Knows about recent advances in distributed systems (e.g., MapReduce, MPP Architectures, External Partitioning)
6. Asks correct questions when data model and requirements are not well defined and comes up with designs which are scalable, maintainable and efficient
7. Makes enhancements that improve team’s data architecture, making it better and easier to maintain (e.g., data auditing solutions, automating, ad-hoc or manual operation steps)
8. Owns the data quality of important datasets and any new changes/enhancements
A day in the life
This role requires you to live at the intersection of data, software, and analytics. We leverage a comprehensive suite of AWS technologies, with key tools including S3, Redshift, DynamoDB, Lambda, API's, Glue. You will drive the development process from design to release.
Managing data ingestion from heterogeneous data sources, with automated data quality checks.
Creating scalable data models for effective data processing, storage, retrieval, and archiving.
Using scripting for automation and tool development, which is scalable, reusable, and maintainable.
Providing infrastructure for self serve analytics and science use cases.
Using industry best practices in building CI/CD pipelines
About the team
Demand Science Optimization (DSO) team builds software systems in the realm of Machine Learning (ML/AI/LLM) and economic modeling to address specific device-related challenges within inventory management functions: demand forecasting, pricing, and allocation. Our goal is to achieve a high level of automation, enabling a hands-off approach to assess tradeoffs such as pricing and promotion strategies, prediction and optimization services, and economic valuation. This approach aims to expedite the operational and financial leverage of Devices and Services, enhance customer satisfaction, and direct our team's expertise towards strategic decisions that have lasting implications. With a diverse product portfolio including popular devices like Alexa, Kindle, Ereader, Ring, Blink, and more, DSO faces intricate challenges. Our software solutions wield considerable influence, as our predictive algorithms guide the allocation of billions of dollars across a multitude of distribution points globally.
