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 The Digital Execution Lead, you will be responsible for the design, development, and optimization of end-to-end data pipelines and architectures. You will ensure the integrity, security, and performance of the organization’s data ecosystem by building scalable ETL/ELT workflows, maintaining advanced cloud data warehouses, and implementing data governance protocols. As a technical leader, you will collaborate with cross-functional teams to enable advanced analytics and machine learning capabilities through reliable, high-quality data infrastructure.
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.
****Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $163000 - $237000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Design, build, and optimize automated workflows for construction technology and AEC software utilization in Data center Design and construction. Build ETL and ELT pipelines to move data from various source systems into centralized cloud repositories.
- Architect and maintain high-performance cloud data warehouses and lakehouses, ensuring efficient database schema design and cost-effective storage.
- Implement digital delivery strategy for faster and efficient data center build. Develop draft data quality frameworks, automated validation checks, and strict security controls to ensure data trustworthiness and regulatory compliance.
- Manage complex data dependencies using workflow orchestration tools like Apache Airflow and deploy proactive system monitoring and alerting.
- Collaborate with Data Analysts and Scientists to build pre-aggregated data models and feature stores that accelerate business intelligence and model deployment.
Qualifications
Minimum qualifications:
- Bachelor’s degree in Computer Science, Data Science, Software Engineering, or a related quantitative field, or equivalent practical experience.
- 5 years of experience in program management.
- 5 years of experience in data engineering, building and maintaining production-grade ETL/ELT pipelines.
- 5 years of experience in programming languages such as Python, Java, or Scala.
- 5 years of experience with BigQuery and dashboarding tools for analysis insight.
- 5 years of experience with SQL including window functions, query optimization, and data modeling.
Preferred qualifications:
- Master’s degree in Computer Science or a relevant engineering discipline.
- 5 years of experience managing cross-functional or cross-team projects.
- Experience with AI tools and large-scale data governance frameworks for security and compliance.
- Advanced experience in architecting solutions in cloud environments like Google Cloud, etc.
- Proficiency with workflow orchestrators like Apache Airflow and modern transformation tools like dbt.
- Strong understanding of DevOps practices including Git, Docker, Kubernetes, and automated CI/CD pipelines.