Minimum qualifications:
- Bachelor's degree in an engineering discipline, Construction Management, or equivalent practical experience.
- 5 years of experience working with data center or other mission critical equipment/environments.
- 5 years of experience managing process improvement or construction programs in a matrixed environment.
Preferred qualifications:
- Master's degree in Engineering, Business Administration, or a related field.
- Experience in managing and executing projects, serving in a program role supporting back office operations, and working across various stakeholders and teams.
- Knowledge of large-scale mission critical facility’s electrical and mechanical infrastructure systems.
About the job
Google's projects, like our users, span the globe and require managers to keep the big picture in focus while being able to dive into the unique engineering challenges we face daily. As a Technical Program Manager at Google, you lead complex, multi-disciplinary engineering projects using your engineering expertise. You plan requirements with internal customers and usher projects through the entire project lifecycle. This includes managing project schedules, identifying risks and clearly communicating them to project stakeholders. You're equally at home explaining your team's analyses and recommendations to executives as you are discussing the technical trade-offs in product development with engineers.
Using your extensive technical and leadership expertise, you manage projects of various size and scope, identifying future opportunities, improving processes and driving the technical directions of your programs.
As the Technical Program Manager, you will be involved in multiple strategic programs focused on improving our data center planning and execution. Within the Third Party Data Center (3PDC) environment, you will act as an interface between the construction delivery leads, engineering leads, developer contract holders, DC supply planning team members, and internal stakeholders and vendors to ensure ML allocation and improvement initiatives are supported. Additionally, you will organize and manage program initiatives through completion including successfully delivering and communicating operational improvements, machine learning progress, and project delivery updates to the business. These program initiatives will focus on the processes, procedures, and tools within the programmatic end-to-end data center delivery plan and execution process.
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.
The US base salary range for this full-time position is $163,000-$237,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Participate in and create a program initiative charter, working with internal stakeholders to strategize, plan, and prioritize objectives and success criteria; estimate task durations; ensure schedules and dependencies are aligned; and support those objectives.
- Seek approval of the program initiative and support requests. Work with teams to identify resources best suited to participate and contribute to an initiative project.
- Manage, monitor, and communicate progress, risks, and mitigations of the project initiative during the development and execution phase.
- Ensure that all goals and objectives of the initiative are successfully met with clear implementation strategy, quantifiable impacts to the site teams, and recorded risks prior to completion of the initiative.
- Report leadership consumption on ML progress, mitigations, and learnings.
