Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 5 years of experience with technical program management.
• 5 years of experience in capacity/supply/demand planning, operations, construction, or supply chain/planning program management within a data center environment.
  
• Experience with the software development lifecycle and product launches.

Preferred qualifications:

• Experience working with Engineering teams spanning hardware and software.
  
• Experience managing engineering projects with cross-team and cross-functional interactions/implications.

About the job

Project Services focuses on making sure every project has the resources and knowledge to deliver on-time with an acceptable risk profile. Central Programs is how the team extracts efficiency across the portfolio through standardization, consistent data structures, rationalized processes, and tools that help automate.

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.

Responsibilities

• Work across the Tooling team in order to ensure all optimized processes are implemented within the enterprise tooling framework.
  
• Lead the delivery, implementation, and business change management of construction-related tools and processes for the global Google Data Center organization.
• Drive creation of artifacts for a typical Software Development Lifecycle (SDLC) program such as requirement documents, business benefits, design document, project plan, risk assessment, scope, timeline, resourcing, budget, change management, and communication plan.
• Work with unstructured data sets to get insights from data sources and develop solutions for scalable reporting, including building and evaluating data models that automate decision-making.
• Enhance operational workflows, tools, and systems through data analysis, technical knowledge, and efficient process improvement.