Lead Data Technical Program Manager

Google•Papillion, NE

3d•$138,000 - $198,000

About The Position

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. Google's Data Center, Compliance, Strategy and Risk Management team (CSRM) is a dedicated organization chartered with protecting the people and assets of Google’s global critical infrastructure. As a Lead Data Technical Program Manager, you will help develop a culture where security, risk, and resiliency are integrated into every facet of Google, including the creative process. You will help us continually identify, evaluate and monitor enterprise risks that could affect business activities and provide business leaders the information they need to make critical decisions. You will collaborate with cross-functional teams to create innovative strategies and develop industry leading programs that drive sustainable effectiveness. The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide. We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Requirements

Bachelor's degree or equivalent practical experience.
2 years of experience in data management, data engineering, data analytics, or technical program management.
Experience in developing and implementing data strategies and governance frameworks.
Experience with data quality management and ensuring data resilience.
Experience with data modeling and investigative techniques.

Nice To Haves

6 years of experience in a data-focused role within a large-scale technology environment.
Experience with building and maintaining large-scale data pipelines and ecosystems.
Experience with predictive analysis and machine learning applications in a business context.
Strong understanding of compliance, risk, or assurance reporting needs.
Demonstrated ability to synthesize complex data into clear, actionable insights for stakeholders, including executive leadership.
Ability to drive data standardization and influence data practices across multiple teams.

Responsibilities

Define and execute the data strategy and governance framework, working with internal and external stakeholders to identify and develop standardized datasets for cross-functional reporting on risk, assurance, and compliance.
Drive data standardization initiatives within and across partner organizations to ensure consistency, scalability, and support for tooling and reporting needs.
Implement and manage processes for data hygiene and resilience, including monitoring, auditing, and governing data quality and relevance. Identify and address broken data pipelines, poor data quality, missing inputs, structural errors, and changing data sources.
Develop data models and predictive analysis systems using high-quality data to analyze historical trends, forecast future outcomes, and provide insights that drive key business decisions.
Collaborate with engineering and product teams to integrate data solutions and ensure data integrity across various platforms.