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The role involves four key areas of responsibility: capacity planning and execution, leadership support and technical expertise, data-driven decision making and operational effectiveness, and cross-functional collaboration and communication. The primary objectives include developing and executing infra capacity plans, providing technical proficiency to leaders, analyzing data to inform capacity decisions, and driving long-term capacity roadmap planning. Additionally, the role requires building robust relationships with internal partners, drafting technical communications, and representing the VP of capacity product management in executive leadership discussions. Overall, the role demands a strategic and collaborative approach to drive business outcomes and ensure alignment with internal and customer needs.
Job Responsibility:
Develop, ratify, and execute infra capacity ops and strategic plans, ensuring internal and customer alignment
Mitigate risks and develop mitigation strategies
Provide technical expertise to prepare leaders for internal and external meetings
Represent VP of capacity product management in executive leadership XFN discussions
Create documents and presentations to frame important decisions and initiatives
Measure effectiveness, collect insights, and analyze data to inform capacity decisions
Drive long-term capacity roadmap planning with partner organizations
Scope, manage, execute, and track priority workstreams on behalf of leadership
Define cohesive operations strategy to bolster PM team efficiency and effectiveness
Leverage and influence cross-functional relationships to drive touch points and leadership processes
Build effective working relationships with internal partners (Finance, HR, product, etc.)
Draft routine technical communications for internal posts, All-Hands, Q&As, etc
Requirements:
Bachelor's degree in a directly related field, or equivalent practical experience
12+ years work experience or equivalent degree involving analytical and operational rigor as typically seen in, but not limited to, functions such as management strategy consulting, finance, business operations, project management, or sales planning and operations
Experience working with cross-functional teams in a large scale technology or hyperscaler environment
Experience and familiarity with data center capacity planning, prioritization and management
Experience in aligning and managing stakeholders at executive levels
Experience leading multiple complex projects and tasks under tight timelines and shifting priorities
Demonstrated experience context switching and connecting the dots across many different topics and stakeholders
Demonstrated experience synthesizing information into a clear and cohesive narrative
Demonstrated understanding of hyperscale capacity allocation methodology and interdependencies as well as the supporting tools
Demonstrated people management, influencing and coaching skills, with direct and cross-functional teams
Experience building and scaling entirely new initiatives or programs, from defining the strategy to execution and management post-launch
Demonstrated communication and presentation skills with an emphasis on translating insights and data into actionable recommendations for leaders
Demonstrated problem solving and analysis skills, experience solving complex and multifaceted business problems (commercial, operational, organizational)
Experience effectively navigating through ambiguity and complexity to overcome obstacles with little to moderate direction
Demonstrable success as a leader of change, achieving operational improvements and success by introducing new performance measures, processes and systems
Experience working directly with leadership and stakeholders at all levels, including executive and C-suite, both inside and outside of an organization
Experience handling highly confidential information
Nice to have:
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies