Technical Program Manager Data Analytics

Minimum qualifications:

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
  
• 8 years of experience with program management in leading cross-functional projects/programs.
  

Preferred qualifications:

• 8 years of experience with data analytics, reports/dashboard, and data pipelines using SQL or Python.
  
• 5 years of experience with Technical Program Management in a data-related domain.
  
• Experience managing teams/data engineers to develop analytics solutions and lead data operations.
  
• Experience building and deploying data governance practices.

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.

Responsibilities

• Work cross-functionally with global geographically distributed program managers, data engineers, and data scientists to understand, implement, and deploy actionable analytics solutions.
  
• Establish an operations measurement framework and develop and execute a long-term strategy.
  
• Drive improvements for both system and process to achieve data integrity, data transparency, and a positive user experience.
  
• Provide mentorship/coaching to other team members.
  
• Drive system and process development to improve the quality of analytics products with respect to data security, data quality, and data privacy.