Data Engineer, AWS Marketplace

Amazon Dev Center U.S., Inc.
 Seattle, WA

Desciption

Job summary

AWS Marketplace is changing the way AWS customers discover, deploy, and pay for software. Any AWS customer can easily find software on the AWS Marketplace website, deploy it immediately, and be metered for usage that appears directly on their AWS bill. Buyers can quickly buy the software they need and sellers have access to millions of customers of AWS.

As a Data Engineer on the AWS Marketplace team you will work directly with Software Engineering, Business Intelligence, Data Science and Product teams to continuously improve our of data infrastructure, design, tools and pipelines. Your work will directly influence and drive organizational insights, customer facing features and machine learning models.

To be successful in this role, you should have strong database design skills, comfort with large data sets and an eagerness to invent. You should have a passion for data and analytics with the technical skills needed to build for scale and automation.

A day in the life

  • Collaborate with Software Engineers, Product Managers, Data Scientists and Business Intelligence Engineers to design, plan and deliver on high priority data initiatives serving internal stakeholders and AWS customers.
  • Build automated data processing solutions leveraging Spark, EMR, Python, Redshift and S3.
  • Look around corners and be creative - Continuously evaluate and improve our strategy, architecture, tooling and codebase to maximize performance, scalability and availability.

About the hiring group

Inclusive Team Culture

Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Work/Life Balance

Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

Mentorship & Career Growth

Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.

Job responsibilities

Basic Qualifications

  • Bachelor’s degree in Computer Science or a related field
  • 5+ years of experience in Data Engineering / Data Warehousing
  • 5+ years experience with SQL
  • 2+ years experience with Big Data Technologies (Spark, EMR, Spectrum, Glue etc.)
  • 2+ years of experience with Python, Java or similar programming languages.

Preffered Qualifications

  • Experience with Redshift, S3, Glue, Spectrum, EMR, DynamoDB, Kinesis.
  • Experience building TB-PB scalable data solutions
  • Experience in building large scale distributed data processing pipelines

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.

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