Technical Program Manager III, Data Infrastructure, Google Cloud
Sunnyvale, CA, USA; Mountain View, CA, USA
Minimum qualifications:
- Bachelor's degree in a technical field, or equivalent practical experience.
- 5 years of experience building scalable and sustainable tools and platforms for Machine Learning (ML).
- 5 years of experience in program management.
Preferred qualifications:
- 5 years of experience managing cross-functional or cross-team projects.
- Experience building user-facing data tools through collaboration with customers.
- Knowledge of ML data infrastructure.
- Ability to identify and address potential issues with the usage of ML data tools.
About the job
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.
Our goal is to build a Google that looks like the world around us — and we want Googlers to stay and grow when they join us. As part of our efforts to build a Google for everyone, we build diversity, equity, and inclusion into our work and we aim to cultivate a sense of belonging throughout the company.
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.
The US base salary range for this full-time position is $142,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.The US base salary range for this full-time position is $142,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Collaborate with engineering, product management, and cross-functional partners to define work-streams, requirements, schedule, resourcing, and milestones.
- Plan features and build cohesion and alignment across stakeholders.
- Communicate project status to different audiences, including cross-functional teams and executives.
- Identify, develop, and implement process improvements to help the team.
- Resolve issues and help identify and implement risk mitigation, manage important customer engagements, promote the ML Data Platform, and identify KPIs and data quality metrics for success.
Tags: Architecture Data quality Engineering GCP Google Cloud KPIs Machine Learning
Perks/benefits: Career development Equity / stock options Salary bonus
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