Data Engineer, AWS Payments Data Platform

Amazon Web Services
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Job Description

The AWS Payments Loss Mitigation and data infrastructure team is looking for savvy Data Engineers to join our growing team of engineers and business analysts. This role will be responsible for improving and optimizing our data and data pipeline architecture, and optimizing data flow and collection for cross functional teams within Commerce Platform. The ideal candidate is an experienced data pipeline builder who is passionate and adept at building highly optimized data systems from the ground up.

As a Data Engineer, you will directly support business analysts, product managers, software developers, and Data Science teams on data and analytics initiatives. You will build secure, sustainable, and data systems and analytics processes that can be leveraged across the organization. You should be self-directed and comfortable supporting the data needs of multiple teams. The right candidate will be excited by the prospect of optimizing or even re-designing our organization's data architecture to support the next generation of products and analytics.

A day in the life

Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well-balanced life—both in and outside of work.

We have a formal mentor search application that lets you find a mentor that works best for you based on location, job family, job level etc. Your manager can also help you find a mentor or two, because two is better than one. In addition to formal mentors, we work and train together so that we are always learning from one another, and we celebrate and support the career progression of our team members.

Here at , 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 we 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 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Learn more about Amazon on our Day 1 Blog:

About the hiring group

Job responsibilities

  • Assemble large, complex data sets that meet functional and non-functional business requirements.
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, security, etc.
  • Develop and improve data reporting and data quality systems and applications
  • Develop and maintain fully automated pipelines (CICD)
  • Ensure consistent data security and access control across multiple regions
  • Drive and contribute to team technical strategies to improve data systems, analytics processes, and ETL/ELT processes
  • Build analytics tools that utilize data pipelines to uncover actionable insights that improve the customer experience, increase revenue, improve operational efficiency, and other KPIs.
  • Communicate effectively and collaborate with multiple executives, product teams, software development teams, and end users to solve complex data-related technical issues and support their data needs
  • Work effectively on an Agile data team and collaborate with other data teams to drive organization wide efficiencies
  • Triage data research requests and issues for effective resolution


  • 5+ years of experience in a Data Engineer role and a Bachelor's degree in Computer Science, Statistics, Information Systems or other quantitative field
  • Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
  • Experience with data modeling, data warehousing, and building ETL pipelines
  • Advanced working SQL knowledge and experience working with relational databases
  • Intermediate level skill using , Scala, , other language for data processing and data analysis
  • Familiarity with /Unix scripting
  • Experience building and optimizing ‘big data’ pipelines, architectures and data sets
  • Experience using big data technologies (, Hive, Hbase, Spark, EMR, etc.)
  • Working experience implementing full CICD pipelines
  • Experience performing root cause analysis on data and processes to answer specific business questions and identify opportunities for improvement
  • Strong analytic skills related to working with structured and unstructured datasets
  • Experience using analytics and dashboarding tool like Tableau, Excel/Power BI, Jupyter Notebooks, etc)


  • Master's degree in Computer Science, Statistics, Information Systems or other quantitative field
  • Experience working with big data technologies (EMR, Redshift, S3, Glue, Kinesis and Lambda for Serverless ETL)
  • Working knowledge of message queuing, stream processing, and highly ‘big data’ data stores
  • Strong project management and organizational skills
  • Experience supporting and working with cross-functional teams in a dynamic environment
  • Continuous improvement mindset and analytical skills to research and adapt new technologies and methodologies.

Company Info.

Amazon Web Services

Amazon Web Services, Inc. (AWS) is a subsidiary of Amazon providing on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered pay-as-you-go basis. These cloud computing web services provide a variety of basic abstract technical infrastructure and distributed computing building blocks and tools. One of these services is Amazon Elastic Compute Cloud (EC2).

  • Industry
    Information Technology
  • No. of Employees
  • Location
    410 Terry Ave N, Seattle, WA, USA
  • Website
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