Privacy Engineering Leader: AI/ML & Strategy

Google

San Francisco (CA)

On-site

USD 207,000 - 300,000

Full time

35 hours ago
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Job summary

Google is seeking a Privacy Engineering Manager to lead the GBO Privacy Working Group within the Global Go-to-Market organization. You will oversee privacy program development across partnerships, sales and support teams worldwide, ensuring regulatory compliance and protecting user trust while enabling business growth.

You will manage a high-performing team, translate complex privacy requirements for executive stakeholders, and explore AI/ML tools to streamline review processes and enhance

Qualifications

  • 7 years of experience in a privacy related field (e.g., security engineering, data engineering, data scientist, compliance engineering).
  • 2 years of experience managing, mentoring, and developing a team to drive initiatives and solutions with company-wide impact.
  • 2 years of experience managing resources to solve technical and operational problems and customize solutions.

Responsibilities

  • Lead the team responsible for developing, shaping, and maintaining the privacy program for GBO.
  • Partner with teams across GBO to develop privacy safe designs and complete launch reviews for compliance.
  • Partner with executive leadership to launch and scale strategic privacy initiatives with data-driven updates.
  • Identify opportunities to optimize PWG operations by integrating AI/ML tools into the review lifecycle.

Skills

Bachelor's degree
Privacy experience
Team leadership
Resource management

Education

Bachelor's degree or equivalent

Job description

Google is seeking a Privacy Engineering Manager to lead the GBO Privacy Working Group within the Global Go-to-Market organization. You will oversee privacy program development across partnerships, sales and support teams worldwide, ensuring regulatory compliance and protecting user trust while enabling business growth.

You will manage a high-performing team, translate complex privacy requirements for executive stakeholders, and explore AI/ML tools to streamline review processes and enhance

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