Senior Technical Program Manager, GDCO Intelligence and Analytics Team

Job :  | Amazon Data Services, Inc.

We're looking for a Senior Technical Product/Program Manager to own a portfolio of these business-facing products and programs end to end: shaping what each one should do and for whom, driving its design and delivery with engineering, science and data technicians, and proving it changes business outcomes. This role is oriented toward business problems and the products/programs that solve them, not toward running shared platform infrastructure.

You'll be as comfortable reviewing a system architecture or challenging a recommendations quality as presenting a roadmap to senior executives like VPs.

• Self-service analytics, to production. Take our natural-language and SQL analytics product over the governed data lake from team tool to a production service leaders rely on: accuracy on governed metrics, onboarding new domains, reliability, access controls, and adoption.
• Recommendation engine delivery and quality. Deliver the AI-assisted recommendation engine from pilot to broad use, own its quality bar: what it recommends, with what confidence, when it should stay silent, and how we know it worked.
• Business domain decision products. Our operation runs on a few core business domains, each with its own leaders, metrics, data sources, and decisions. For each one, you'll own the product that moves a leader from "what's happening" to "what should I do about it": define the decisions it supports, the metrics and data it needs, and how we measure whether it improved the domain's outcome.
  
  Today that means: data products that cover repair backlog and aging, repair throughput and turnaround time, parts availability and other blockers, and repeat failures. The core decision is where to focus the effort so it returns the most capacity to customers fastest. Data products track deliveries from plan through install and hand-off, show what's on track, what's at risk, and why (parts, labor, facilities, network readiness), and route each blocker to the owner who can clear it.
  
  The core decision is which at-risk deliveries need intervention now. Success is more capacity delivered on its committed date.

• Own program strategy and roadmap for each product/program in the portfolio, tied to a business outcome (repair turnaround, labor productivity, capacity on time), and phase scope deliberately from pilot to GA.
• Define and enforce quality. Set the bar for each products/programs, such as answer accuracy for self-service analytics or recommendation precision, confidence, and abstain behavior for the recommendation engine. Partner with engineering and science so no product presents correlation as causation or claims more confidence than it has earned.
• Prove business impact. Define how actions are captured, how impact is measured against matched baselines, and how outcomes feed back into the product. Success is not "recommendations accepted" or "queries run"; it's decisions that changed outcomes.
• Run technical delivery with the engineering team. Own the delivery cadence, sprint planning, and release management for your products/programs. Review design docs, understand the architecture well enough to weigh tradeoffs (build vs. reuse, latency vs. cost, coupling between services), and keep scope, sequencing, and dependencies honest.
• Drive launch readiness across security review, penetration testing, operational readiness (ORR), and privacy reviews for each product moving to production.
• Lead cross-org dependencies with Supply Chain, Hardware Engineering, Facilities, workforce planning, and peer data teams: write the asks, negotiate data contracts, and elevate when a…