AI-Driven Pipeline & Revenue Planning Lead

Amazon; Mountain View (CA); On-site; USD 147,000 - 199,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon's AWS ASP Ops is seeking a Sr. Pipeline & Revenue Planning Lead in Mountain View to own quarterly pipeline forecasting and revenue-to-pipeline bridge analytics, ensuring data-driven targets for Specialists and Partners.

You will design end-to-end planning, integrate data sources, and partner with Data Science, Finance, and BI teams to deliver scalable, AI-enabled forecasting mechanisms in a fast-changing business.

Qualifications

• 7+ years in sales/revenue ops or business planning with pipeline ownership.
• Ability to analyze complex data and turn it into actionable deliverables.
• Experience building forecasting models combining math and business judgment.
• Cross-functional work with Sales, Finance, and Data/BI to forecast targets.
• Experience with BI tools such as QuickSight, Tableau or Power BI.
• Experience implementing AI-enabled automation in forecasting workflows.

Responsibilities

• Own the quarterly pipeline forecasting and target-setting mechanism.
• Build revenue-to-pipeline bridges linking bookings, revenue, and pipeline.
• Collaborate across ASP Ops, SMGS Ops, and Finance to govern scalable forecasts.
• Own metrics readiness for new partner revenue measures with planning teams.
• Identify forecast divergence, diagnose root causes, and advise leadership.
• Translate analytics outputs into clear, action-ready recommendations.

Skills

Forecasting

Data analysis

Cross-functional collaboration

Quarterly forecasting

Revenue planning

AI-enabled automation

Tools

QuickSight

Tableau

Power BI

Job description

Amazon's AWS ASP Ops is seeking a Sr. Pipeline & Revenue Planning Lead in Mountain View to own quarterly pipeline forecasting and revenue-to-pipeline bridge analytics, ensuring data-driven targets for Specialists and Partners.

You will design end-to-end planning, integrate data sources, and partner with Data Science, Finance, and BI teams to deliver scalable, AI-enabled forecasting mechanisms in a fast-changing business.