Program Manager III, Logistics Capacity Planning, Cloud Logistics
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience in program or project management.
- Experience in developing forecasting models and scripting in SQL.
- Experience in logistics, logistics capacity planning, network modeling, constraint planning, or demand forecasting.
Preferred qualifications:
- Experience building and owning end-to-end quantitative logistics capacity, network, constraint, or forecasting models across warehousing, distribution centers, data center operations, or hardware supply chains.
- Expertise in physical logistics capacity and distribution planning, modeling network flows, sourcing rule changes, storage footprint, dock throughput, and labor capacity across short and long-term horizons.
- Advanced proficiency in SQL, Python, or statistical modeling tools to build capacity pipelines, simulate network/sourcing changes, analyze plan-vs-actual variances, and improve forecast accuracy (WAPE, MAPE, Bias).
- Define business logic, sourcing rules, and functional requirements that integrate and automate manual planning models into internal logistics capacity planning tooling.
About the job
A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Program Manager at Google, you’ll lead complex, multi-disciplinary projects from start to finish — working with stakeholders to plan requirements, manage project schedules, identify risks, and communicate clearly with cross-functional partners across the company. Your projects will often span offices, time zones, and hemispheres. It's your job to coordinate the players and keep them up to date on progress and deadlines.
The Google Cloud Logistics (GCL) Capacity Planning team ensures the operational readiness and scalability of Google's global logistics network. In this role, you will own end-to-end capacity planning, transforming demand forecasts into executable operational plans. You will bridge supply chain strategy and on-the-ground execution by designing and owning the quantitative models that govern network flow, storage, throughput, and labor. You will use SQL, data pipelines, and analytical models to simulate sourcing changes, stress-test network capacity (e.g., space, dock throughput, labor), and run scenarios to balance workloads. You will establish and lead planning cycles, including regional Demand-Supply Reviews (DSR) with Operations and third-party logistics (3PL) partners, integrating commitments into monthly S&OP/D&OP processes. You will also partner with Engineering and Product teams as a subject matter expert to codify business logic and network constraints into automated, scalable planning tools.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $159000 - $230000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Build network flow and distribution models across upstream suppliers, regional fulfillment hubs, and destination data centers; evaluate sourcing rule changes, lane realignments, and routing adjustments to assess downstream capacity impacts and balance network workload.
- Establish and govern repeatable capacity planning processes, planning calendars, and forecast lock cycles from the ground up, embedding warehouse and data center capacity plans into monthly S&OP/D&OP cycles, rolling commits, and quarterly/annual budgeting.
- Own key forecast health metrics, including plan-vs-actual variance and forecast accuracy/bias (WAPE, MAPE), driving root-cause analysis and continuous calibration of the underlying models and parameters that enable constraint planning.
- Design, build, and own forecasting and capacity models that enable constraint planning across GCL global warehouses and data centers, translating upstream supply chain and deployment schedules into multi-horizon plans across storage space, dock throughput, and labor.
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