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Data EngineerAmazon Web Services, Inc. • Seattle, Washington, United States
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Data Engineer

Amazon Web Services, Inc.
  • US
    Seattle, Washington, United States
  • US
    Seattle, Washington, United States
Jetzt Bewerben

Über

Sales, Marketing and Global Services (SMGS)
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.
Mission Statement The AWS Marketing Data: AI Science, Analytics and Engineering (D:SE) team owns analytics, reporting and self-service tooling, data representation, machine learning models, measurement, valuation and economics products for AWS Marketing. We are the central data and science organization, and we work with different teams in AWS Marketing to drive better measurement, increase experimentation velocity, improve data access and analytical self-service, deploy and test ML-powered targeting models, drive higher economic value, and empower strategic decisions with business deep dives. We enable other analytics, BI, and science teams across AWS Marketing through mechanisms, partnerships and scalable tools. We work globally as a central team and establish standards, benchmarks, and best practices for use throughout AWS Marketing.
Overview Would you like to support increasing customer base and the revenue for AWS, a market-leading cloud offering? Would you like to be part of a team focused on increasing awareness and adoption of the AWS platform by analyzing customer's behavior on and outside AWS websites? Do you want to empower our AWS Marketing organization make data-driven decisions that further establish AWS as leader in the cloud computing world?
A day in the life
Design, implement, and support a platform providing ad-hoc access to large datasets
Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL
Build robust and scalable data integration (ETL) pipelines using SQL, Python and AWS services such as Data Pipelines, Glue
Implement data structures using best practices in data modeling, ETL/ELT processes, and SQL/Redshift
Interface with business customers, gathering requirements and delivering complete reporting solutions
Build and deliver high quality datasets to support business analyst and customer reporting needs
Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
Location Successful candidate must be located in Seattle - WA / Austin - TX / New York - NY / Herndon - VA.
About the team About AWS: Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the 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.
Inclusive Team Culture: Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & 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.
Work/Life Balance: We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Basic Qualifications
Bachelor's degree
3+ years of data engineering experience
2+ years of developing and operating large-scale data structures for business intelligence analytics (using ETL/ELT processes) experience
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)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers.
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  • Seattle, Washington, United States

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  • English
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