Demand Planner
Listed on 2026-07-03
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IT/Tech
Data Engineering, Data Analyst, Data Warehousing
What We Offer
- Flexible time off policy
- 401K Company match (up to 4% - dollar for dollar)
- Professional development, training, and tuition reimbursement programs
- Excellent medical, dental, vision, and life insurance policy options
- Opportunities for career advancement with an industry leading company!
The Demand Planner – Data Center leads the end-to-end demand planning cycle for AFL’s Data Center Business Unit within the Integrated Business Planning (IBP) framework. This role sits within AFL’s enterprise demand planning function and carries primary accountability for the demand signal serving AFL’s five global hyperscaler customers — Amazon, Microsoft, Google, Oracle, and Meta — whose investment cycles, construction pipelines, and capacity ramp timelines drive the majority of demand complexity in this portfolio.
The Data Center demand environment is characterized by lumpy, project-based order patterns tied to hyperscale capital expenditure cycles, rapid market growth and structural demand volatility, and a fast-moving product portfolio shaped by continuously evolving connectivity requirements. Reporting to the Director of Demand Planning, the Demand Planner – Data Center operates within AFL’s IBP standards and governance while applying a high degree of independent judgment to navigate these unique dynamics.
This role is a recognized functional expert in project-based demand planning and a key contributor to the accuracy and integrity of the Data Center demand signal across the enterprise.
- Deliver a reliable rolling 36-month unconstrained demand plan for the Data Center hyperscale portfolio each IBP cycle, consistently meeting cadence requirements and enterprise standards.
- Develop and operationalize a project-tracking demand overlay methodology that translates hyperscale construction pipeline signals and Cap Ex announcements into structured, decision-ready demand inputs within the first two IBP cycles.
- Drive measurable improvement in Forecast Value Added (FVA) quality for the Data Center portfolio, with documented root-cause insights on lumpy order variability shared back to the broader planning team.
- Build and maintain a market intelligence library — covering hyperscale earnings guidance, Cap Ex trends, and data center construction pipeline signals — that systematically strengthens the Data Center demand baseline.
- Support at least one major new product introduction (NPI) with a structured demand ramp plan, aligned with IBP financial reconciliation.
- Informally mentor at least one junior planner in AFL’s IBP methodology, with a focus on project-based demand pattern analysis.
- Lead the end-to-end execution of the demand planning cycle for the Data Center hyperscale portfolio in line with the enterprise IBP cadence, managing the unique complexity of project-based, capital-cycle-driven demand from AFL’s five global hyperscale accounts (Amazon, Microsoft, Google, Oracle, and Meta).
- Generate, refine, and publish statistical and consensus demand plans at the Customer x SKU x Month level, incorporating both statistical baseline and project-based demand overlays to capture lumpy, non-recurring volume patterns.
- Develop and maintain a structured project-tracking methodology that translates hyperscale construction pipeline intelligence, purchase orders, and capacity ramp signals into decision-ready demand inputs aligned with IBP governance.
- Produce decision-ready Demand Review pre-reads for the Data Center portfolio — including KPIs, assumptions logs, structured action registers, and project pipeline summaries — with minimal direction.
- Maintain accurate planning hierarchies, segmentation, and master data for the Data Center portfolio in coordination with enterprise standards.
- Coordinate with peer planners to ensure the Data Center demand signal integrates cleanly into the consolidated Product Solutions demand view, resolving methodology inconsistencies at the interface.
- Apply and extend the enterprise forecasting methodology to the high-variability, project-based Data Center demand…
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