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Sr Manager, Data Engineering , Amazon Selling Partner Verification
Seattle, WA, USA
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On-site
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Full-time
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1w ago
As the leader of the Seller Verification Services (VS) Data function, you will drive the transformation of Amazon's global seller verification and onboarding systems. VS operates at the intersection of trust and scale—enabling legitimate sellers to onboard quickly while preventing bad actors from accessing the Amazon marketplace. Our organization combines engineering, analytics, product management, and program expertise to verify millions of entities annually.
You will lead the data infrastructure that powers verification decisions across Amazon's worldwide stores. This includes building scalable data pipelines, developing analytical frameworks, and enabling machine learning models that assess seller legitimacy in real-time. Your work will directly impact seller experience, marketplace integrity, and Amazon's ability to grow its third-party selling business globally.
The Sr Manager, Data Engineering role owns a portfolio of data engineering, business intelligence, and analytics teams that solve complex verification challenges. You will partner with product managers, software engineers, data scientists, and business leaders to deliver data infrastructure, modeling capabilities, and insights that drive verification effectiveness. This role requires proven people management experience and the ability to define and execute strategy across a global technical ecosystem.
The ideal candidate excels at building simple, elegant solutions that scale. You think holistically across organizational boundaries, translating business problems into technical solutions. You create collaborative outcomes, ensure systems are reliable and secure, and always prioritize the customer experience.
Key job responsibilities
As Sr Manager of Data Engineering, you will lead multiple teams of builders to define and deliver the Verification Services data strategy:
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Set organizational priorities by balancing customer experience, stakeholder requirements, and business impact. Define success metrics and ensure teams focus on high-leverage work.
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Define the long-term technical vision for data infrastructure, analytics, and machine learning enablement. Design systems that scale with business growth and adapt to evolving verification requirements.
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Deliver high-quality data engineering solutions including production-grade pipelines, data models, and analytical tools. Build rapid prototypes to validate approaches and gather user feedback.
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Collaborate with product and business leaders to translate verification requirements into technical solutions. Partner with science teams to productionize models and with engineering teams to integrate data systems.
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Hire and develop talent across data engineering, business intelligence, and analytics disciplines. Build a high-performing organization capable of solving Amazon's most complex verification challenges.
About the team
The Verification Services team has evolved over 8+ years through scope expansion and organizational integration. Our leadership team brings diverse backgrounds in engineering, product, program management, operations, science, and business intelligence.
Basic Qualifications
- Bachelor's degree
- 8+ years of data engineering experience
- 5+ years of engineering team management experience
- Experience managing multiple projects and priorities across teams in a fast-paced, deadline-driven environment
- Experience leading global teams
Preferred Qualifications
- Experience working with data engineers and business intelligence engineers collaboratively
- 3+ years of identity verification/fraud detection process experience
- Experience building large-scale machine learning and AI solutions at Internet scale
- Experience in regulatory compliance management with government agencies
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, WA, Seattle - 202,300.00 - 273,700.00 USD annually
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About Amazon

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
Employees
Seattle
Headquarters
Reviews
2.9
10 reviews
Work Life Balance
2.8
Compensation
3.7
Culture
2.5
Career
2.3
Management
2.1
35%
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Pros
Good pay and compensation
Strong benefits package
Flexible scheduling options
Cons
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
Salary Ranges
2 data points
L2
L3
L4
L5
L6
L2 · Data Analyst L2
0 reports
$108,330
total / year
Base
$43,332
Stock
$54,165
Bonus
$10,833
$75,831
$140,829
Interview Experience
10 interviews
Difficulty
3.7
/ 5
Duration
21-35 weeks
Offer Rate
20%
Experience
Positive 10%
Neutral 10%
Negative 80%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
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