Technical Program Manager II, Supply Chain Analytics, Google Ads

Minimum qualifications:

• Bachelor's degree in a technical field, or equivalent practical experience.
• 2 years of experience in program management.
• Experience in supply chain management in one or more of the following functions, such as capacity planning, technical infrastructure, or hardware transformation.

Preferred qualifications:

• 2 years of experience managing cross-functional or cross-team projects.
• Experience with cloud technologies, data centers, or machine learning supply chains.
• Experience in mathematical modeling.
• Familiarity with Sales and Operations Planning (S&OP) and forecasting processes.
• Strong data analysis skills, including proficiency in SQL, dashboards, and data modeling.

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.

The Ads Allocation team sits at the nexus of Ads supply and demand planning for non-ML resources. We have invested over 2 years of work streamlining and integrating team decision support tools, but there are still some cases where more sophisticated analysis or deeper integration are required to improve forecast accuracy and thereby support product safety with thinner margins. Successful completion of this pivot will require detailed data and process analysis, discovering or updating key sources of truth, integrating deep knowledge of the end-to-end non-ML resource planning processes, creation and curation of key team automation, while juggling normal day-to-day operations and out-of-cycle escalations.

Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.

The US base salary range for this full-time position is $138,000-$198,000 + 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

• Collaborate with team members and stakeholders to understand or identify defined work problems and program goals, obtain prioritized deliverables, and discuss program impact.
• Review key metrics pertaining to a program, monitor potential metric deviations, and define corrective actions for critical deviations to manage resource and power escalations.
• Develop tooling and analysis to streamline Ads PARM decision support to improve Ads spatial flexibility, (e.g., service migrations and other infrastructure changes/adoption).
• Develop tooling and automation to curate the data that supports team process automation and execution.
• Collaborate with Global Infrastructure Group (GIG) and Capital Engineering (CapEng) (e.g., supply side) and Ads and anchor footprint planners (e.g., demand side) to build and execute credible plans of record for Ads non-ML resource provisioning.