Technical Program Manager II, Network Demand Analytics, Cloud Networking

Build, maintain, and optimize complex queries, automated scripts, and interactive reporting dashboards to generate the demand plan, visualize network demand trends, and surface business insights.Lead the development of internal tools and data pipelines. Leverage scripting and back-end data manipulation to automate manual workflows, reduce planning cycle times, and drive the transition toward autonomous planning.Design and implement the backend data structures and reporting frameworks required to seamlessly operationalize the demand and forecasting processes for new network products and architectures.Act as the bridge between technical and business teams. Partner closely with engineering, data science, and planning groups to translate organizational OKRs into scalable data models and BI solutions, while balancing competing priorities.Minimum qualifications:Bachelor's degree in a technical field, or equivalent practical experience. 2 years of experience in program management.Experience with tooling and automation development. Experience working with data analytics tools (e.g., SQL, BigQuery, R, etc.) and reporting platforms (e.g., Tableau, Microstrategy, Business Objects, etc.).Preferred qualifications:2 years of experience managing cross-functional or cross-team projects.Experience extracting and manipulating data and writing automation scripts to streamline workflows (e.g., SQL, Python, Appscript, etc.).Experience managing cross-functional projects and driving alignment between technical and non-technical stakeholders.Experience developing interactive reporting dashboards and working with BI visualization tools.Passion for learning new AI frameworks, rapid prototyping, with the ability to drive results.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. In this role, you will be the technical engine behind Google’s network demand planning. You will design, build, and maintain the business intelligence infrastructure, reporting dashboards, and data pipelines necessary to optimize our demand plan. You will deliver forecast accuracy and drive towards autonomous planning, you will write scripts to automate complex data workflows, manipulate large datasets within back-end tables, and extract insights into network demand trends. You will partner closely with Cloud Networking product, data science, engineering, and planning teams to translate complex business requirements into technical solutions, automated processes, and scalable data models.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.Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $138000 - $198000 (USD) + 15% bonus target + equity + benefitsLearn more about benefits at Google.Bachelor's degree in a technical field, or equivalent practical experience. 2 years of experience in program management.Experience with tooling and automation development. Experience working with data analytics tools (e.g., SQL, BigQuery, R, etc.) and reporting platforms (e.g., Tableau, Microstrategy, Business Objects, etc.).