Data Engineer, AWS Sustainability Technology
Job Description
The Data Engineer role within AWS Sustainability Technology focuses on building data models, ETL pipelines, and predictive analytics to support energy, renewable resources, sustainability, and water portfolios, enabling informed decision making and decarbonization efforts. This onsite opportunity is based in Seattle, WA, with a salary range of USD 132,100 to 178,800 per year.
Responsibilities
- Develop large-scale data models for clients in energy, renewable resources, sustainability, and water sectors to evaluate portfolio performance and risks.
- Collaborate with data scientists to enable the creation and deployment of predictive models that enhance decision making.
Requirements
- 3+ years of data engineering experience.
- At least 1 year developing and operating large-scale BI data structures for analytics using ETL/ELT processes.
- At least 1 year developing and operating large-scale BI data structures using OLAP technologies.
- At least 1 year of experience in data modeling for BI environments.
- At least 1 year of SQL experience in BI contexts.
- At least 1 year of Oracle experience.
- Experience with data modeling, warehousing, and building ETL pipelines.
Technologies
- Redshift
- S3
- AWS Glue
- EMR
- Kinesis
- FireHose
- Lambda
- IAM
- Oracle
- SQL
Benefits
- Sign-on payments
- Restricted stock units (RSUs)
- Health insurance (medical, dental, vision, prescription)
- 401(k) matching
- Paid time off
- Parental leave
- Basic Life and AD&D insurance
- Supplemental life plans
- Employee Assistance Program (EAP) and mental health support
- Flexible Spending Accounts
- Adoption and surrogacy reimbursement coverage
Description
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In this role, the team supports all AWS data centers and the servers, storage, networking, power, and cooling equipment that ensure customers have continual access to cloud services. The group tackles the most challenging problems, with thousands of variables impacting the supply chain.