Senior Data Engineer, Partner Intelligence

Found in: Talent US C2 - 2 weeks ago

Seattle, United States Amazon Web Services, Inc. Full time
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.

The AWS Partner Intelligence team is seeking a Senior Data Engineer to help design, deploy and scale a suite of next generation data and governance solutions supporting a high impact community of Science and Analytics builders. This is a high-visibility position focused on enabling Scientists, BIEs and SDEs with robust, secure and highly reliable data tools and assets that support internal and Partner-facing solutions. In this role you will work with directly with senior builders, leaders and business stakeholder to dive deep on the status quo and make bold, long-term recommendations on strategic direction and solution designs.

10010

Key job responsibilities
- Approach ambiguity with open arms and lean in on your strong judgement and technical background to deliver impactful, incrementally hardened solutions.

- Define and deploy development and tooling standards for upstream providers and internal stakeholders

- Have an implicit passion for delivering data of an exceptionally high quality standard and strong security posture.

About the team
The Partner Intelligence team is a robust centralized Analytics and Science community supporting the AWS Partner Organization on its mission to provide customers with a unified, outstanding experience while working with AWS partners.

About AWS

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.

Why 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.

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.

We are open to hiring candidates to work out of one of the following locations:

Atlanta, GA, USA | Austin, TX, USA | New Jersey, NJ, USA | Seattle, WA, USA

BASIC QUALIFICATIONS

- 5+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience mentoring team members on best practices
- Design & Implementation of automated data contract and data quality enforcement mechanisms

PREFERRED QUALIFICATIONS

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience building world-class data environments with a high emphasis on data quality and data security.

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