Amazon Web Services, Inc.
Technology
DataEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Engineer at Amazon Web Services, Inc.. Skills: Data engineering, Data warehousing, ETL pipelines. Design platform providing ad-hoc access to large datasets. Implement platform providing ad-hoc access to large datasets”
Industry & Context.
Data-driven decisions
What They're Looking For.
Must Have
3+ years of data engineering experience, 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes, 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling, 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL, Experience with data modeling, Experience with warehousing, Experience building ETL pipelines
Nice to Have
Experience with AWS technologies, Experience with non-relational databases
What You'll Do.
Design platform providing ad-hoc access to large datasets
Implement platform providing ad-hoc access to large datasets
Support platform providing ad-hoc access to large datasets
Extract data from wide variety of data sources
Transform data from wide variety of data sources
Load data from wide variety of data sources
Build scalable data integration pipelines
Implement data structures using best practices
Interface with business customers
Deliver complete reporting solutions
Build high quality datasets
Deliver high quality datasets
Improve ongoing reporting processes
Improve ongoing analysis processes
Automate self-service support for customers
Simplify self-service support for customers
How You'll Work.
Team & Collaboration
Technology teams; Business customers
Full Job Description
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? As a Data Engineer at AWS, you will be working in a large, extremely complex and dynamic data warehousing environment. We are looking for someone with the uncanny ability to integrate mult
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