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Amazon Data Engineer, Global Demand & Operations in Austin, Texas

Description

AWS Global Demand & Operations (GDO) team is seeking a Data Engineer to empower business decision making along Lead Flow Process by building our owned data service. You will contribute and build GDO's next-generation data repository, offer data solution for optimizing lead flow process. If you are passionate about building data platform/pipeline solutions for AWS Global Demand & Operations central team, please join us!

We’re on the lookout for the curious, those who think big and want to define the world of tomorrow.

At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with exciting new challenges, developing new skills, and achieving personal growth.

How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow.

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.

Key job responsibilities

As a data engineer, you will/may:

• Design, implement, and automate deployment of our distributed system for collecting and processing log events from multiple sources.

• Design data schema and operate internal data warehouses and SQL/NoSQL database systems.

• Own the design, development, and maintenance of ongoing metrics, reports, analyses, and dashboards that engineers, analysts, and data scientists use to drive key business decisions.

• Monitor and troubleshoot operational or data issues in the data pipelines.

• Drive architectural plans and implementation for future data storage, reporting, and analytic solutions.

• Develop code based automated data pipelines able to process millions of data points.

• Improve database and data warehouse performance by tuning inefficient queries.

• Work collaboratively with Business Analysts, Data Scientists, and other internal partners to identify opportunities/problems.

• Provide assistance to the team with troubleshooting, researching the root cause, and thoroughly resolving defects in the event of a problem.

A day in the life

About the team

ABOUT AWS:

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

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.

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.

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 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

  • Experience with data modeling, warehousing and building ETL pipelines

  • 2+ years of data engineering, database engineering, business intelligence or business analytics experience

  • Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS

Preferred Qualifications

  • Master’s Degree or advanced technical degree

  • Prior experience with AWS

  • Experience building large scale data pipelines and/or automated ETL processes

  • Experience with big data processing technology (e.g., Hadoop or ApacheSpark), data warehouse technical architecture, infrastructure components, and reporting/analytic tools and environments

  • Basic understanding of Machine Learning concepts and techniques

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $91,200/year in our lowest geographic market up to $185,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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