Want to get hired at Google?

Data and AI Manager

Google

Warsaw, Mazowieckie, PolandOn Site

Original Job Summary

About the Role

Google is seeking a Data and AI Manager to lead Global Services Delivery in the Google Cloud division. In this role, you will drive data-driven management, collaborate with product and engineering teams, and work with customer stakeholders on critical solution decisions.

Minimum Qualifications

  • Bachelor's degree in STEM or equivalent practical experience.
  • 7 years in solution engineering/architecture.
  • 5 years in stakeholder management or technical consulting.
  • 5 years delivering customer-facing Data and AI services.
  • 2 years managing technical teams in cloud computing or customer-facing roles.

Preferred Qualifications

  • Master's degree in Engineering, Computer Science, or related fields.
  • Experience with recommendation engines, data pipelines, or distributed machine learning.
  • Consulting experience with diverse customers and teams.
  • Background in software development and professional services.
  • Knowledge of TensorFlow and other AI frameworks.
  • Proven leadership in designing custom AI-based cloud solutions.

Responsibilities

  • Provide data-driven management in a dynamic environment.
  • Collaborate with cross-functional Google Cloud AI teams.
  • Engage with customer stakeholders as a trusted advisor.
  • Shape strategic direction with Account Teams and Sales.

Key Skills/Competency

  • Data Management
  • AI
  • Customer Engagement
  • Cloud Computing
  • Technical Consulting
  • Solution Engineering
  • Machine Learning
  • Strategic Planning
  • Team Leadership
  • Analytics

How to Get Hired at Google

🎯 Tips for Getting Hired

  • Research Google Cloud: Understand Google culture and services.
  • Customize your resume: Highlight technical and leadership roles.
  • Showcase projects: Detail Data and AI implementations.
  • Prepare for interviews: Focus on solution engineering and team management insights.

📝 Interview Preparation Advice

Technical Preparation

Review cloud computing fundamentals and architectures.
Study AI frameworks like TensorFlow and ML pipelines.
Brush up on solution engineering case studies.
Practice technical problem-solving scenarios.

Behavioral Questions

Describe a challenge in team management.
How do you handle cross-department conflicts?
Explain customer stakeholder engagement experience.
Discuss adapting strategies under pressure.