Amazon Senior Data Engineer AWS Sustainability Tech 

United States, Washington, Seattle 

666064574

You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.We recently announced that AWS will be water positive by 2030, returning more water to communities than it uses in its direct operations. To learn more about AWS’s water+ commitment visit: Water Stewardship.Key job responsibilities
Our Data Engineers develop large data models for clients in energy, renewable resources, sustainability, and water sectors, enabling them to assess their portfolios. They help our data scientists create predictive models to enhance decision-making.A day in the life
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Work/Life BalanceMentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

- 5+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience mentoring team members on best practices

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience operating large data warehouses