Data Engineer, AWS Monetization

Amazon

Seattle, WA, USA Remote

Full time

Engineering

May 5

DESCRIPTION

Job summary

Are you interested in building the next generation, cloud-based commerce system for AWS that’s used by millions of customers worldwide? Are you excited by the idea of building real-time stream processing systems that operate at Petabyte scale? Do you want to make an impact at a $10-billion-a-year business? Then we need to talk!


About the hiring group

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. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.


Job responsibilities

The successful candidate will be an analytical problem solver who enjoys diving into data, is excited about solving ambiguity problems, can multi-task, and can credibly interface between technical teams and business stakeholders.


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.

BASIC QUALIFICATIONS

  • This position requires a Bachelor's Degree in Computer Science or a related technical field
  • 5+ years of work experience with ETL, Data Modeling, and Data Architecture.
  • Expert-level skills in writing and optimizing SQL.
  • Experience with AWS products including Big Data Technologies (Redshift, RDS, S3, Glue, Athena, EMR, Spark, Hive, etc.)
  • Proficiency in one of the scripting languages - Python, Scala, Java or similar.
  • Experience working with very large data warehouses or data lakes.

PREFERRED QUALIFICATIONS

  • Experience with data visualization using Tableau, QuickSight, or similar tools
  • Authoritative in ETL optimization, designing, coding, and tuning big data processes using Apache Spark or similar technologies.
  • Experience with building data pipelines and applications to stream and process datasets at low latency.
  • Knowledge of Engineering and Operational Excellence using standard methodologies.



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.

Apply for this position Back to job

You must be logged in to to apply to this job.

Apply

Your application has been successfully submitted.

Please fix the errors below and resubmit.

Something went wrong. Please try again later or contact us.

Personal Information

Profile

View resume

Details

Amazon

Work hard, Have fun, Make History

{{notification.msg}}