Level

Amazon

Sr. Manager, Data and Insights, US Prime & Marketing Technology

AI in this role

Leading a team to build AI-native analytics and agent-ready data foundations for customer insights.

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Are you excited to build and grow a new customer insights team that will influence flagship initiatives across Amazon and Prime? Do you enjoy using data, analytics, and AI to deliver actionable insights that support critical business decisions?

The US Prime & Marketing Team is seeking an experienced data and analytics leader to lead and grow a new North American Stores Customer Insights team focused on delivering faster, AI-accelerated insights and recommendations that drive customer engagement across North American Stores and US Prime.

As the Sr. Manager, Data and Insights, you will lead a multidisciplinary team of Business Analysts, Business Intelligence Engineers, and Data Engineers who provide data, reporting, and analytical insights that influence and support critical business decisions. You will create and implement a new charter that reimagines how insights are generated and delivered, combining traditional BI with agentic, AI-native analytics: conversational access to trusted data, automated deep dives, and agent-ready data foundations that get answers to decision-makers in hours instead of weeks. You will build scalable data solutions to enable insight generation and provide analytical support for flagship initiatives across Amazon and Prime. You will lead the team to design and build the right data infrastructure layer, including well-governed, semantically documented data that both humans and AI agents can trust and consume, to enable reporting and analytics, while partnering with product teams to define metrics, software engineering teams to instrument the appropriate data pipelines, and data engineering to scale our data infrastructure.

You will lead the team to build the AI layer of the insights stack, not just adopt it: standing up the data services and agent integrations that let internal AI tools query our data safely, developing and improving natural-language reporting so partners get answers directly, and setting the standard for how BAs, BIEs, and DEs use AI-assisted tooling in their own work. The goal is to move team capacity from routine reporting to the deep analysis and recommendations that move the business.

This role requires excellent technical skills and hands-on fluency with how GenAI is changing analytics work, in order to raise the bar on both the team's craft and its high-judgment, responsible use of AI, and excellent written/verbal communication skills to interact effectively with business and tech leadership.

Key job responsibilities
- Single-threaded owner for data, analytics, insights, and AI-enabled analytics for the US Prime & Marketing Technology team
- Lead and coach a multidisciplinary team of Business Intelligence Engineers, Business Analysts, and Data Engineers, setting the standard for how each role applies AI-assisted tooling in their own work
- Develop, launch, and scale self-service analytics and insights offerings, including natural-language and conversational access to data that lets partners get trusted answers directly
- Design and build the governed data models, semantic layers, and agent integrations that allow internal AI assistants and agents to consume NA Stores and Prime data reliably
- Deliver insights and recommendations to help shape strategy across North American Stores and US Prime, moving team capacity from routine reporting toward deep analysis and high-judgment recommendations
- Partner with Business, Product, Marketing, Finance, Engineering, and Science leaders to provide data-driven insights and recommendations that influence business decisions

About the team
Few analytics teams at Amazon get a domain this wide. US Prime & Marketing Technology (UPMT) owns the US Prime member experience, the category, seasonal, and brand marketing and creative for North America Stores, and the science and engineering behind the automated and agentic merchandising, personalization, and content-quality platforms that run across Amazon's stores worldwide. Our belief is that everything beautiful should be automated, and everything automated should be beautiful. Measuring an org like that means working across membership economics, marketing incrementality, on-site and off-site engagement, creative performance, and the output of agentic systems that didn't exist two years ago.


Basic qualifications

- Bachelor's degree
- 11+ years of as a Data Analyst, Data Engineer, Business Intelligence Analyst, or a related occupation experience
- 5+ years of delivering results managing a business intelligence or analytics team, including employee development and performance management experience
- Experience in scripting for automation (e.g. Python) and advanced SQL skills.
- Experience with data modeling, warehousing and building ETL pipelines
- Experience interpreting data and making business recommendations across leadership and cross-functional teams

Preferred qualifications

- Master's degree or above in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field, or Master's degree and 5+ years of a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science experience
- Experience defining roadmap strategy and prioritizing deliverables for your team products
- Experience managing analytics, data science or technology teams, with a product or insight focus
- Experience with data analytics platforms (Power BI, Python, SQL, Tableau), or experience with advanced use of SQL for data mining and business intelligence
- Experience leading a team that built GenAI-enabled analytics products on AWS, such as conversational access to data or agentic analytical workflows
- Experience building governed semantic layers, metrics stores, or data models that make organizational data reliably consumable by AI agents and natural-language analytics
- Experience with causal measurement at scale, such as incrementality testing, marketing mix modeling, geo-experiments, or subscription and membership LTV analysis
- Experience leading a multidisciplinary team that includes Data Engineers alongside Business Intelligence Engineers and Business Analysts

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 - 170,600.00 - 230,800.00 USD annually

How we rate this

Sr. Manager, Data and Insights, US Prime & Marketing Technology at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

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Skills and AI tools this role asks for

AI AgentsData AnalysisBusiness IntelligenceData EngineeringGenerative AIAgentic WorkflowsAmazon Quick

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. Tell me about a project where data analysis was part of your work. What did you do?
  3. Tell me about a project where business intelligence was part of your work. What did you do?
  4. Tell me about a project where data engineering was part of your work. What did you do?
  5. Tell me about a project where generative ai was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI Agents, Data Analysis, Business Intelligence, Data Engineering, and Generative AI. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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