Application deadline: Nov 10, 2026
AWS is seeking a Senior Product Manager to define and drive the product strategy for the Partner analytics portfolio within AWS Specialist & Partner (ASP). This team builds the data products, reporting systems, and analytics experiences that help AWS's partner organization operate - from goal-setting and planning through execution tracking and business reviews. The work sits at the intersection of product management, data strategy, and partner operations, in an environment where AI-powered automation is increasingly how the team delivers value rather than a future-state aspiration.
The Senior PM owns the end-to-end product lifecycle for the team's analytics portfolio: defining what gets built, sequencing the roadmap, and partnering across field teams, programs, finance, and GTM to ship products that make partner-facing roles more effective. This means translating ambiguous operational problems into well-scoped products - dashboards, planning tools, self-service analytics, automated reporting - and increasingly, AI-assisted experiences that surface insights at the point of decision. The right candidate brings strong product management fundamentals, comfort navigating a complex stakeholder landscape, and the judgment to distinguish between problems that need a product and problems that need a process.
Key job responsibilities
1. Owns the product strategy, roadmap, and requirements for the partner analytics portfolio - reporting, data products, planning tools, and AI-powered analytics that serve partner-facing field roles across ASP. Determines what to build, defer, and deprecate.
2. Translates complex partner operations workflows into prioritized product requirements - goal cascades, territory planning, program tracking, business review content, adoption analytics - balancing stakeholder needs against technical feasibility and delivery timelines.
3. Establishes a shared product vision across the organization by engaging stakeholders and ensuring the roadmap reflects both customer needs and business priorities. Creates buy-in for that vision internally and with cross-functional partners.
4. Partners closely with BIE leads and data engineering to foster a collaborative, delivery-focused culture - shaping what the team builds while empowering builders to own how it gets built. Influences data architecture decisions, KPI definitions, and governance frameworks without owning them directly.
5. Identifies analytics and data products that help field roles execute more effectively - partner development, program tracking, business reviews, planning workflows - and translates those opportunities into scoped products that serve each role's workflow.
6. Drives cross-functional alignment across finance, GTM, programs, and field teams - building shared context on priorities, dependencies, and trade-offs so that the analytics portfolio reflects actual operational needs rather than a queue of ad-hoc requests.
7. Shapes the team's AI and agentic strategy - evaluating where LLM-powered agents, natural language interfaces, and intelligent automation can augment field productivity and surface insights at the point of decision. Drives those capabilities from concept through adoption.
8. Determines what to automate and what to deprecate - identifies manual, repetitive operational work that can be replaced by product (automated reporting, self-service analytics, intelligent alerting, AI-assisted planning) and sequences those capabilities into the roadmap based on impact and feasibility.
9. Defines and tracks product health metrics - adoption, engagement, stakeholder satisfaction, automation coverage, cycle time reduction - using them to prioritize the roadmap and demonstrate impact to leadership.
10. Owns communication with leadership and cross-org partner teams - writes narratives that frame product capability in terms of business outcomes, presents trade-offs clearly in business reviews, and builds the credibility to influence how the organization invests in analytics and AI.
A day in the life
You will start your morning reviewing product metrics and customer feedback to identify emerging patterns. From there, you might refine a working-backwards document with your engineering and design partners, then join a roadmap review where you present trade-off recommendations to leadership. Afternoons could involve usability testing sessions, sprint planning with developers, or stakeholder syncs to align on priorities across teams. Throughout it all, you are the connective thread between customer insight and product execution.
About the team
The PARK (Partner Analytics & Reporting Knowledge) team within ASP Insights owns the end-to-end analytics architecture for AWS's global partner organization - data platforms, governance frameworks, self-service products, and the AI integration layer that connects them. We serve thousands of stakeholders across partner sales, operations, and leadership, and we're actively evolving from traditional BI toward systems where intelligent automation handles the default case and human expertise focuses on strategy and exceptions. This role shapes that evolution - setting technical standards, making architecture decisions, and raising the bar for what the team builds.
BASIC QUALIFICATIONS
- 5+ years of product or program management, product marketing, business development or technology experience
- Bachelor's degree or equivalent
- Experience owning/driving roadmap strategy and definition
- Experience with feature delivery and tradeoffs of a product
- Experience working with data-intensive products: analytics platforms, BI tools, planning systems, or operational reporting
PREFERRED QUALIFICATIONS
- Experience in influencing senior leadership through data driven insights
- Experience working across functional teams and senior stakeholders
- Experience in a partner ecosystem, channel operations, GTM, or sales operations environment where analytics directly connects to field execution and revenue outcomes
- Experience building products that automate or augment manual business workflows - planning tools, goal-setting systems, self-service reporting, operational dashboards
- Familiarity with AI/ML capabilities relevant to analytics products - agentic workflows, LLM-powered interfaces, intelligent alerting, recommendation systems, or natural language query
- Experience with business review cadences, operational planning cycles, or field enablement - understanding how analytics products plug into how an organization actually runs
- Track record of defining and shipping products in ambiguous problem spaces where the product definition and the organizational process co-evolve
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, CA, Mountain View - 152,200.00 - 206,000.00 USD annually
USA, CO, Denver - 136,000.00 - 184,100.00 USD annually
USA, NY, New York - 152,200.00 - 206,000.00 USD annually
USA, WA, Seattle - 136,000.00 - 184,100.00 USD annually
