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Amazon Data Engineer WWPS Products Engineering 
United States, Virginia 
606812882

09.09.2024
DESCRIPTION

Key job responsibilities
* You will define advancements to the architecture.
* You will review and provide guidance on when to leverage the latest AWS technologies.
* You will work directly with the software engineering teams to optimize the ingestion of current and future data sets.
* You will evolve the data platform to support new applications and use cases; such as analytics, modeling for Gen AI features, and reporting.
* You will define and manage an ETL process into a central AWS data warehouse; making the appropriate data sets available across WWPS.
* You will set a high bar for availability and resilience in production.A day in the life
As a specialist in data engineering, you wear many hats to support the organization.* You work hands-on with SDEs to structure and manage data coming into the data platform.
* You focus on operational excellence, assuring the appropriate monitors are in place to assure the success of ETL jobs, data hygiene, and general availability of the data platform.
* You carve out time to stay up to speed on relevant AWS technologies (S3, DynamoDB, Redshift, Glue, Kinesis, to name a few), data management best practices, and AI with an eye towards understand what will be needed next.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.Why AWS
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.


BASIC QUALIFICATIONS

- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines