Machine Learning Data Engineer, WW Sustainability

4 weeks ago


Seattle, Washington, United States Amazon Full time
About the Role

Amazon is seeking a highly skilled Data Engineer to join our Worldwide Sustainability (WWS) organization. As a key member of our Sustainability Science and Innovation team, you will play a critical role in building the data foundation of the future.

As a Data Engineer, you will be responsible for designing, implementing, and maintaining data infrastructure to support a wide variety of large and complex data sets. You will work closely with Machine Learning and Environmental Scientists to identify, ingest, harmonize, store, and maintain strategic data from both internal and external sources.

The ideal candidate will have experience with data modeling, warehousing, and building ETL pipelines, as well as knowledge of professional software engineering and best practices for full software development life cycle. Experience with AWS technologies, non-relational databases, and modern scripting or programming languages is a plus.

As a Data Engineer on our team, you will have the opportunity to work on end-to-end projects independently and partner with Scientists and Software Engineers to create our data collection strategy and ML Ops best practices.

We value diverse experiences and encourage candidates from all backgrounds to apply. If you are a hands-on leader and innovator at the intersection of AI, data, and sustainability, we'd like to connect with you.

About the Team

Our team is committed to creating a culture of inclusion that empowers us to be proud of our differences. We believe in ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, to inspire us to never stop embracing our uniqueness.

We also prioritize work-life harmony, offering flexible work hours and arrangements to support our employees' well-being. Our team is dedicated to achieving success at work without sacrificing our personal lives.

Basic Qualifications
  • 3+ years of data engineering experience
  • Experience with data modeling, warehousing, and building ETL pipelines
  • Knowledge of professional software engineering and best practices for full software development life cycle
Preferred Qualifications
  • Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
  • Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
  • Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
  • Experience working on and delivering end-to-end projects independently


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