The role
From Google's own posting.
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 at Google, you will lead multi-disciplinary projects for Google’s Data Center teams. You will plan requirements with internal customers and support projects through the entire project life-cycle, manage project schedules, identify risks, and communicate goals to project stakeholders. You will work with stakeholders to architect, execute, and deliver data ingestion, leadership visualizations and insights, data warehouse infrastructure and data models, and advanced analytics leveraging ML/AI. You will manage program schedules, highlight risks, and communicate goals.
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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $163000 - $236000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google .
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.
Lead multiple data-solution programs, including coding responsibilities 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.
Manage all aspects of program deliverables from project inception to implementation and resource oversight.
Manage datasets to extract business insights that help 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 Information Systems, Computer Science, Data Science, Analytics, Mathematics, or equivalent practical experience.
5 years of experience in program management.
Experience in SQL, Python, or BigQuery.
Experience in advanced analytics or AI/ML model-based solutions, and data engineering or systems management (e.g., data warehousing, data analytics, business intelligence, visualization, data governance, data architecture, and system integration).
Preferred qualifications:
5 years of experience managing cross-functional or cross-team projects.
Experience in modern data warehouses using cloud based solutions from data sources, predictive analytics, or machine learning.
Experience leading and delivering data-focused programs.
Experience with executing change management or program strategy.
Experience in developing batch and real time streaming data pipelines using Google Cloud Platform BigQuery, Dataflow, and Publish/Subscribe from data sources (e.g., Oracle, SAP).
Bachelor’s degree in Information Systems, Computer Science, Data Science, Analytics, Mathematics, or equivalent practical experience.
5 years of experience in program management.
Experience in SQL, Python, or BigQuery.
Experience in advanced analytics or AI/ML model-based solutions, and data engineering or systems management (e.g., data warehousing, data analytics, business intelligence, visualization, data governance, data architecture, and system integration).