About the job

A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you’ll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You’ll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.

As a Technical Program Manager, you will lead, architect, design, build, and implement data warehouse infrastructure, data structures, data engineering processes, visualizations and data analytics, and drive quality/consistency. You will facilitate data availability across multiple functional domains and systems. You will work with Data Center stakeholders to understand their data issues and challenges, build and deploy simple, efficient, secure, and scalable data solutions, services, insights, and analytics. You will manage a portfolio of programs that help teams successfully operate, while transforming the organization by building and integrating the next wave of data solutions.

Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.

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

• Lead multiple data-solution programs covering data pipelines, visualizations, data alerts, advanced analytics, and machine learning methods, translating raw data into strategic insights and recommendations for leadership and business teams.

• Design and implement data warehouse infrastructure, data structures, batch and real-time data pipelines, predictive analytics and machine learning models using Google Cloud Platform (GCP), translate data and model results into strategic insights for leadership and business stakeholders.

• Manage all aspects of program deliverables from project inception to implementation and resource oversight.

• Work on large datasets to extract business insights that directly help to maintain up-time of critical data center operations, and increase operating efficiency of teams responsible for designing and building Google’s data center footprint.

Minimum qualifications

• Bachelor's degree in a technical field, or equivalent practical experience.

• 2 years of experience in program management.

• Experience developing or deploying advanced Analytics and Machine Learning model based solutions using cloud tools and technologies.

• Experience with analytics using frameworks like SQL or Python languages.

Preferred qualifications

• Master's degree in Information Systems, Computer Science, Data Science, Analytics, Mathematics or a related field.

• 2 years of experience managing cross-functional or cross-team projects.

• Experience developing batch and real time streaming data pipelines using GCP bigquery, dataflow and Publish/Subscribe (Pub/Sub) from heterogeneous data sources (e.g., Oracle, SAP, etc.).

• Experience leading organizational change efforts using data tools and solutions to improve organization efficiency.

• Experience in Machine Learning, ML data management and agentic AI tooling.

• Familiarity with ML/AI model based solutions.