Customer Engineer Data and AI Manufacturing @ Google
placeBerlin, Berlin, Germany
attach_money €120,000
businessOn Site
scheduleFull Time
Posted 17 hours ago
Your Application Journey
Interview
Email Hiring Manager
****** @google.com
Recommended after applying
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
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
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Review cloud architecture fundamentals.
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Study machine learning implementation practices.
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Practice data pipeline design techniques.
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Familiarize with Google Cloud platforms.
Behavioral Questions
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Describe a challenging client engagement.
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Explain teamwork on technical projects.
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Discuss conflict resolution with stakeholders.
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Share examples of proactive client support.
Frequently Asked Questions
What qualifications does Google seek for the Customer Engineer Data and AI Manufacturing role?
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How important is technical sales experience for this Customer Engineer role at Google?
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What machine learning or data pipeline skills are required for Google Cloud's Customer Engineer role?
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Does the role require fluency in languages for the Customer Engineer position at Google?
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Where can I apply for the Customer Engineer Data and AI Manufacturing role at Google?
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