Customer Engineer Data and AI Manufacturing
@ Google

Berlin, Berlin, Germany
€120,000
On Site
Full Time
Posted 22 days ago

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Job Details

About the Role

The Customer Engineer Data and AI Manufacturing role at Google Cloud partners with Germany's leading automotive and manufacturing companies. It focuses on leveraging data analytics and AI to solve complex industry challenges and to create smart factories and intelligent vehicles.

Minimum Qualifications

  • Bachelor's degree or equivalent practical experience.
  • 4 years of experience in program management, client service or management consulting.
  • Experience applying cloud technologies in manufacturing or automotive industries.
  • Experience designing and implementing machine learning architectures or data pipelines.
  • Experience in technical sales or consulting, including full technical discovery and solution architecture.

Preferred Qualifications

  • Master's degree in Computer Science or related field.
  • Experience with cloud computing, Data Analytics, Big Data and AI.
  • Proficiency in both German and English.

Responsibilities

  • Build and nurture technical relationships with client decision-makers.
  • Guide technical evaluations and develop proof-of-concept solutions.
  • Lead technical presentations and workshops using Google Cloud platforms.
  • Collaborate with sales teams to design and present technical solutions.
  • Advocate customer feedback to improve Google Cloud products.

Key skills/competency

Cloud, Data, AI, Manufacturing, Technical Sales, Consulting, Machine Learning, Relationship Building, Technical Presentation, Client Service

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How to Get Hired at Google

🎯 Tips for Getting Hired

  • Customize resume: Highlight cloud and manufacturing experience.
  • Research Google Cloud: Understand products and technical trends.
  • Prepare case studies: Showcase data pipeline implementations.
  • Practice bilingual skills: Brush up on German technical terms.

📝 Interview Preparation Advice

Technical Preparation

Review cloud architecture fundamentals.
Study machine learning implementation practices.
Practice data pipeline design techniques.
Familiarize with Google Cloud platforms.

Behavioral Questions

Describe a challenging client engagement.
Explain teamwork on technical projects.
Discuss conflict resolution with stakeholders.
Share examples of proactive client support.

Frequently Asked Questions