Senior Product Manager - Technical, Quick Sight - Structured Data Analytics

Amazon is hiring a Senior Product Manager - Technical, Quick Sight - Structured Data Analytics in Seattle, United States. It pays $151k-$205k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this AI product manager role Works on AI ●●●○: the daily work is on AI products, without building the model.
Tools and skills the posting cites include product management, data analytics and natural language processing.
Level classifies it as a senior role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

Lead product strategy for AI-powered data analytics and decision intelligence capabilities in Quick Sight.

product-managementdata-analyticsnatural-language-processingagentic-aicloud-analytics

Amazon Quick is a decision intelligence service for the AI era. Today, thousands of enterprises and millions of users rely on Quick to connect their data, generate insights, and turn decisions into action — whether through interactive dashboards, embedded analytics woven into the products their customers use, natural language experiences that let any knowledge worker ask a question and get an answer they can act on immediately or fully managed tools that they can build and deploy for their stakeholders. Hundreds of ISVs and SaaS companies have already built Quick into the fabric of their applications, powering experiences for millions of end users who benefit from intelligent, data-driven products. That is the kind of reach we operate at — and we are just getting started.

We are now at an inflection point. The convergence of structured data analytics, natural language interfaces, and agentic AI is rewriting the rules of what a decision intelligence service can do — not just for analysts, but for every knowledge worker in an enterprise. Quick sits at the center of this shift. We're building the service that lets an enterprise analyst build a governed dashboard in minutes, an ISV embed AI-powered analytics into their product with a few API calls, and a business leader ask a question in plain English and receive an insight they can turn into action before the day is over. The same service. The same governed data. One experience that scales from a single user to an entire organization — unlocking productivity, surfacing new opportunities, and accelerating businesses that are powered by data.

We are hiring multiple Senior Product Managers in the Quick Sight, the structured data analytics product team to own critical parts of this journey. These roles span some of the most consequential product areas in cloud analytics and decision intelligence today:

- The data and intelligence foundation — how enterprises bring structured and unstructured data together under a unified semantic and governance layer that powers both BI reporting and AI-driven insights that turn into action.
- Embedding and ISV enablement — how thousands of software companies build differentiated, analytics-rich products on top of Quick's capabilities, and how we make that experience so seamless it becomes the default choice for every builder.
- Business model and growth strategy — how we design packaging, pricing, and adoption pathways that make it effortless for customers to start, experiment, and scale with us — turning first deployments into enterprise-wide commitments.

What unites these roles is a shared profile: a deeply technical product leader who is equal parts strategist and practitioner. Someone who can see the three-year arc of a market and then roll up their sleeves to ship the next release. Someone who works backward from the customer's deployment — not from a requirements document — and who measures their own success by whether the customer succeeded. Someone who sees a nascent, fast-growing business not as a risk but as a canvas.

Quick is a business that is growing, evolving, and actively being shaped by the people on this team. You will have a direct and visible thumbprint on a service that is becoming the decision intelligence layer for enterprises and AI-powered products alike. The decisions you make — about what we build, how we package it, who we build it for, and how we bring it to market — will define how thousands of organizations and millions of knowledge workers experience data, make decisions, and take action in the age of AI.

If you are a builder who gets energy from ambiguity, who thinks in systems but ships in increments, and who wants to be at the frontier of where decision intelligence meets artificial intelligence — we want to talk to you.

Key job responsibilities
- Drive product delivery in deep partnership with engineering, applied science, and design. Drive product specifications, make crisp tradeoff decisions, and ensure high bar on the quality and user experience

- Be hands-on with the technology. Whether that means understanding how a semantic model resolves a natural language query, how an embedded analytics SDK integrates into a partner's React app, or how a pricing SKU flows through AWS billing — you operate at the level of detail where real product decisions are made.

- Own the customer journey from first contact through enterprise-wide adoption for critical engagement. Partner with GTM and Sales teams to design onboarding pathways, migration playbooks, and growth motions that reduce friction, accelerate time-to-value, and turn successful deployments into organization-wide productivity gains.

- Engage directly with enterprise customers, ISV partners, and AWS field teams. Turn what you hear into product conviction — not just feature requests, but insight into where the market is moving and what customers will need before they know to ask for it.

- Directly contribute to business outcomes — adoption, revenue, competitive win rates, customer retention. Use data relentlessly to prioritize, to make the case for investment, and to communicate progress to senior leadership.

Basic qualifications

- Bachelor's degree
- Experience owning/driving roadmap strategy and definition
- Experience with feature delivery and tradeoffs of a product
- Experience contributing to engineering discussions around technology decisions and strategy related to a product
- Experience managing technical products or online services
- Experience in representing and advocating for a variety of critical customers and stakeholders during executive-level prioritization and planning

Preferred qualifications

- Experience in using analytical tools, such as Tableau, Qlikview, QuickSight
- Experience in building and driving adoption of new tools

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 - 151,200.00 - 204,600.00 USD annually

How we rate this

Senior Product Manager - Technical, Quick Sight - Structured Data Analytics 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.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

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

Key facts

Senior Product Manager - Technical, Quick Sight - Structured Data Analytics is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The listed salary is $151k-$205k a year.
The role is based in US, WA, Seattle.
The job was posted on May 15, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Product ManagementData AnalyticsNatural Language ProcessingAgentic AICloud Analytics

Also common in AI product manager jobs at this level

AI agents LLM Generative AI Machine learning SQL Azure

Pay

This job starts at: $151k
Typical AI product manager job: $178k

This posting starts 15% below the typical AI product manager job. See AI product manager jobs

Questions you could be asked

Tell me about a project where product management was part of your work. What did you do?
Tell me about a project where data analytics was part of your work. What did you do?
Tell me about a project where natural language processing was part of your work. What did you do?
Tell me about a project where agentic ai was part of your work. What did you do?
Tell me about a project where cloud analytics was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Product Management, Data Analytics, Natural Language Processing, Agentic AI, and Cloud Analytics. 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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