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X The application window will be open until at least August 10, 2026. This opportunity will remain online based on business needs which may be before or after the specified date.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Atlanta, GA, USA; Austin, TX, USA; Addison, TX, USA; Reston, VA, USA; Thornton, CO, USA.

Minimum qualifications:

• Bachelor's degree in a technical field, or equivalent practical experience.
• 8 years of experience in program management.
• 5 years of experience in leadership role with/without direct reports.

Preferred qualifications:

• Bachelor's degree in Information Systems, Computer Science, Data Science, Analytics, or Mathematics.
• 10 years of experience in related disciplines (e.g., Information Systems, Computer Science, Data Science, Analytics, Mathematics).
• 8 years of experience in technical program management in data or systems management, executive-level communications, large-scale change management or program strategy.
• 7 years of experience in architecting data engineering, data warehousing, data analytics, business intelligence, visualization, and complex data solutions using SQL and Python.
• Experience in networking.
• Understanding of data management, data governance, data architecture, data analysis, data profiling, data quality, and system integration, and experience with big data analytics.

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 various Engineering-specific programs and teams.

The Global Infrastructure Delivery (GID) team is responsible for building and operating the production network for Google that provides service to over a billion Internet users around the world. Network Delivery Operations (NDO) is a horizontal team that sits within GID. NDO's three main capabilities are business operations, business intelligence/analytics, and business enablement and is responsible to drive strategy, insights, and solutions which improve infrastructure and network capacity delivery.

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: $192000 - $278000 (USD) 20% bonus target equity benefits

Learn more about benefits at Google .

Responsibilities

• Design, build, and optimize scalable data pipelines and an industry-standard data model, while maintaining the existing data warehouse as a central repository for efficient data retrieval.
• Create and drive the adoption of robust data governance policies, ensuring data access, security, integrity, and high availability in alignment with corporate policy.
• Lead strategic initiatives and apply business knowledge to produce actionable insights, driving cross-functional solutions that reduce cycle times and increase operational efficiency year over year.
• Lead cross-functional stakeholders to drive consensus on data architecture standards and unify KPI and metric definitions, while collaborating with internal teams to advocate for operational needs.
• Provide data engineering leadership and coaching for partner teams, and drive the vendor management strategy, including agreement compliance, execution, and performance oversight.