We are looking for a Principal Modern Planner to own demand planning and forecasting for networking hardware supporting large-scale cloud data center builds and expansions.
This role will connect data center build plans, network architecture, product roadmaps, engineering changes, BOMs, and historical demand to a long-range view of hardware requirements. The planner will work across Networking Engineering, Network Architecture, Data Center Planning, Product, Supply Chain, Procurement, Finance, and Data/Analytics to understand the underlying demand drivers, reconcile different inputs, and improve the quality and consistency of the demand plan.
The role also has a strong analytics and data component. The successful candidate will use forecasting, statistical analysis, data modeling, automation, and AI/ML to improve planning processes, identify issues in the demand signal, and provide better visibility into future capacity and supply requirements.
This is a hands-on Principal role for someone who can move between planning strategy, detailed data analysis, and networking hardware fundamentals, and who can work effectively with both technical teams and senior leadership.
Internal Responsibilities
Own demand planning and forecasting for networking hardware supporting data center builds, expansions, and ongoing capacity requirements.
Develop and maintain long-range demand forecasts, including 24+ month outlooks, across networking products, platforms, and SKUs.
Work with Data Center Planning, Network Engineering, Product, Supply Chain, Procurement, and Finance to understand upcoming builds, deployment timing, architecture changes, and other demand drivers.
Translate data center build plans and network architecture requirements into hardware and component demand, including the relationship between capacity, racks, network topology, BOMs, and SKUs.
Develop forecasting models using historical demand, deployment trends, engineering inputs, product roadmaps, and other relevant signals.
Build scenarios to understand the demand impact of changes in data center build timing, network architecture, product transitions, capacity plans, and supply constraints.
Work with engineering teams to incorporate BOM changes, new product introductions, product transitions, substitutions, and EOL/EOS plans into the forecast.
Identify issues in the demand signal, including double counting, overlapping assumptions, missing requirements, and inconsistent inputs across planning processes.
Establish metrics and analytical methods to measure forecast accuracy, bias, volatility, and confidence, and use those insights to improve the planning process.
Build and maintain the data and analytical foundation needed to connect data center plans, deployment information, engineering/BOM data, demand, supply, and inventory.
Automate recurring planning, reconciliation, and reporting processes using SQL, Python, and other analytical technologies.
Apply statistical forecasting, machine learning, optimization, simulation, and AI where they can materially improve planning quality or reduce manual work.
Establish a regular planning cadence with engineering and business partners, including mechanisms for reviewing assumptions, reconciling changes, and obtaining alignment on the demand plan.
Prepare analysis and recommendations for senior leadership on demand changes, capacity requirements, supply risks, and key planning assumptions.
Lead complex planning issues across organizational boundaries and drive them to resolution.
Mentor other planners and analytical team members and help establish scalable planning practices.
Required Qualifications
Bachelor’s or Master’s degree in Engineering, Computer Science, Data Science, Statistics, Operations Research, Supply Chain, Economics, or a related field.
5-8 years of experience in demand planning, forecasting, capacity planning, supply-chain planning, analytics, operations research, or a related area.
Experience working with technology hardware, networking, semiconductor, cloud infrastructure, or data center infrastructure.
Strong understanding of demand forecasting and long-range planning, including forecast accuracy, bias, scenario planning, and demand drivers.
Experience working with complex hardware products, including BOMs, SKUs, product lifecycle, NPI, EOL/EOS, and product transitions.
Experience connecting engineering, deployment, or infrastructure plans to hardware demand.
Strong analytical and quantitative skills, including hands-on experience with SQL and Python/R.
Experience working with large datasets and using data to investigate problems and support planning decisions.
Strong cross-functional communication skills and experience working with engineering, supply chain, product, and business stakeholders.
Ability to operate independently, navigate ambiguity, and influence decisions across organizations.
Preferred Qualifications
Experience with data center build and deployment planning or cloud infrastructure capacity planning.
Experience with networking hardware such as Ethernet switches, NICs, DPUs/SmartNICs, optical transceivers, cables, or related components.
Familiarity with data center networking architectures and high-performance/AI networking.
Experience developing models that connect data center builds and network architecture to BOM and SKU-level demand.
Experience with networking or semiconductor supply chains, including lead times, constraints, allocation, substitutions, and technology transitions.
Experience with time-series forecasting, probabilistic forecasting, machine learning, optimization, simulation, or other advanced analytical methods.
Experience building data pipelines, analytical datasets, dashboards, or planning tools.
Experience using GenAI or automation to improve planning and forecasting processes.
Experience presenting planning analysis and recommendations to senior engineering or business leadership.
External Responsibilities
Own demand planning and forecasting for networking hardware supporting data center builds, expansions, and ongoing capacity requirements.
Develop and maintain long-range demand forecasts, including 24+ month outlooks, across networking products, platforms, and SKUs.
Work with Data Center Planning, Network Engineering, Product, Supply Chain, Procurement, and Finance to understand upcoming builds, deployment timing, architecture changes, and other demand drivers.
Translate data center build plans and network architecture requirements into hardware and component demand, including the relationship between capacity, racks, network topology, BOMs, and SKUs.
Develop forecasting models using historical demand, deployment trends, engineering inputs, product roadmaps, and other relevant signals.
Build scenarios to understand the demand impact of changes in data center build timing, network architecture, product transitions, capacity plans, and supply constraints.
Work with engineering teams to incorporate BOM changes, new product introductions, product transitions, substitutions, and EOL/EOS plans into the forecast.
Identify issues in the demand signal, including double counting, overlapping assumptions, missing requirements, and inconsistent inputs across planning processes.
Establish metrics and analytical methods to measure forecast accuracy, bias, volatility, and confidence, and use those insights to improve the planning process.
Build and maintain the data and analytical foundation needed to connect data center plans, deployment information, engineering/BOM data, demand, supply, and inventory.
Automate recurring planning, reconciliation, and reporting processes using SQL, Python, and other analytical technologies.
Apply statistical forecasting, machine learning, optimization, simulation, and AI where they can materially improve planning quality or reduce manual work.
Establish a regular planning cadence with engineering and business partners, including mechanisms for reviewing assumptions, reconciling changes, and obtaining alignment on the demand plan.
Prepare analysis and recommendations for senior leadership on demand changes, capacity requirements, supply risks, and key planning assumptions.
Lead complex planning issues across organizational boundaries and drive them to resolution.
Mentor other planners and analytical team members and help establish scalable planning practices.
Required Qualifications
Bachelor’s or Master’s degree in Engineering, Computer Science, Data Science, Statistics, Operations Research, Supply Chain, Economics, or a related field.
5-8 years of experience in demand planning, forecasting, capacity planning, supply-chain planning, analytics, operations research, or a related area.
Experience working with technology hardware, networking, semiconductor, cloud infrastructure, or data center infrastructure.
Strong understanding of demand forecasting and long-range planning, including forecast accuracy, bias, scenario planning, and demand drivers.
Experience working with complex hardware products, including BOMs, SKUs, product lifecycle, NPI, EOL/EOS, and product transitions.
Experience connecting engineering, deployment, or infrastructure plans to hardware demand.
Strong analytical and quantitative skills, including hands-on experience with SQL and Python/R.
Experience working with large datasets and using data to investigate problems and support planning decisions.
Strong cross-functional communication skills and experience working with engineering, supply chain, product, and business stakeholders.
Ability to operate independently, navigate ambiguity, and influence decisions across organizations.
Preferred Qualifications
Experience with data center build and deployment planning or cloud infrastructure capacity planning.
Experience with networking hardware such as Ethernet switches, NICs, DPUs/SmartNICs, optical transceivers, cables, or related components.
Familiarity with data center networking architectures and high-performance/AI networking.
Experience developing models that connect data center builds and network architecture to BOM and SKU-level demand.
Experience with networking or semiconductor supply chains, including lead times, constraints, allocation, substitutions, and technology transitions.
Experience with time-series forecasting, probabilistic forecasting, machine learning, optimization, simulation, or other advanced analytical methods.
Experience building data pipelines, analytical datasets, dashboards, or planning tools.
Experience using GenAI or automation to improve planning and forecasting processes.
Experience presenting planning analysis and recommendations to senior engineering or business leadership.
