Amazon Web Services (AWS)
Data Engineer
Amazon Web Services (AWS)
Description
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. It is the central data and science organization that works 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.
Overview
Would you like to support increasing customer base and revenue for AWS? Would you like to be part of a team focused on increasing awareness and adoption of the AWS platform by analyzing customer behavior on and outside AWS websites? Do you want to empower AWS Marketing to make data-driven decisions that establish AWS as a leader in the cloud computing world?
Key Job Responsibilities
Design, implement, and support a platform providing ad‑hoc access to large datasets
Interface with 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
Basic Qualifications
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, warehousing and building ETL pipelines
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)
Location
Seattle, WA – Successful candidate must be located in Seattle, WA
Job ID
A3139967
Amazon is an equal‑opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information.
Company: Amazon Web Services, Inc.
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Description
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. It is the central data and science organization that works 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.
Overview
Would you like to support increasing customer base and revenue for AWS? Would you like to be part of a team focused on increasing awareness and adoption of the AWS platform by analyzing customer behavior on and outside AWS websites? Do you want to empower AWS Marketing to make data-driven decisions that establish AWS as a leader in the cloud computing world?
Key Job Responsibilities
Design, implement, and support a platform providing ad‑hoc access to large datasets
Interface with 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
Basic Qualifications
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, warehousing and building ETL pipelines
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)
Location
Seattle, WA – Successful candidate must be located in Seattle, WA
Job ID
A3139967
Amazon is an equal‑opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information.
Company: Amazon Web Services, Inc.
#J-18808-Ljbffr