The AWS Sales Marketing Global Services Ops (SMGS Ops) Revenue team publishes mission-critical Sales Revenue data product including, Unified Estimated Revenue, GAAP Sales Revenue, Quota Sales Retirement, and Planning Revenue that power strategic decision-making across AWS Finance, Accounting, Sales Operations, Segmentation Planning & Policy (S&P), Global Sales Compensation, Field Experience, and Data & Analytics teams.
Our platform processes billions of metered usage and billing transactions daily, integrating data from 20+ sources including Salesforce.com to deliver accurate, timely revenue insights that drive quota setting, sales goal management, forecasting, compensation, and business intelligence. We leverage BigData technologies including Elastic Map Reduce (EMR), Spark, Redshift, and Glue and other AWS services to handle massive data volumes at scale.
The Opportunity
We're seeking a passionate Senior Data Engineer to architect and extend our processing framework for next-generation revenue data products. In this high-impact role, you'll:
• Build scalable data pipelines that seamlessly handle exponential data growth and enable rapid development of new revenue products
• Lead AI-driven automation initiatives to transform revenue processing—from data acquisition and validation to publishing and insights generation—into intelligent, systematic workflows
• Architect solutions that enhance data quality, reduce processing latency, and deliver actionable insights to stakeholders across the organization
This role places you at the forefront of innovation, combining big data engineering with AI/ML to revolutionize how AWS processes and reports revenue at global scale.


Key job responsibilities
• Drive technical excellence and organizational growth: Evolve the Revenue technology stack to support AWS's rapid expansion while maintaining compliance with security policies, architectural standards, and operational best practices
• Deliver high-impact data solutions: Design and build end-to-end pipelines that transform raw data from diverse upstream sources into actionable business insights powering quota management, forecasting, and compensation decisions
• Innovate through automation: Develop frameworks, tools, and AI-driven solutions that eliminate manual processes, reduce operational overhead, and accelerate time-to-insight for Revenue customers
• Design scalable data models: Create and maintain dimensional models and data structures that enable self-service analytics and support evolving reporting requirements across Finance, Sales Operations, and Analytics teams
• Lead and mentor engineering talent: Build and guide a high-performing team of Data Engineers to deliver cross-functional solutions, foster technical growth, and establish engineering excellence standards
• Architect and optimize Revenue data infrastructure: Ensure enterprise-grade security, cost efficiency, and scalability while processing billions of daily transactions across 20+ data sources
• Partner across the organization: Collaborate with product managers, stakeholders, and customers to translate business requirements into technical solutions and influence the Revenue product roadmap

About the team
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.

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

Preferred Qualifications

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience operating large data warehouses

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, TX, Dallas - 154,600.00 - 209,100.00 USD annually