Technical Solutions Engineer, Data and AI (Japanese, English)

The Google Cloud team helps companies, schools, and government seamlessly make the switch to Google products and supports them along the way. You solve the technical issues to show how our products can make businesses more collaborative. You work with a cross-functional team of web developers and systems administrators, not to mention a variety of both regional and international customers. Your relationships with customers are important in helping Google grow its cloud business and helping companies around the world innovate.

Responsibilities

• Develop an understanding of Google Cloud's Data Analytics (e.g. BigQuery), AI/ML, and underlying architectures by troubleshooting, reproducing, and determining the root cause for customer reported issues, building tools, and diagnosis.
• Act as a consultant and subject-matter-expert for internal stakeholders in Engineering, Sales, and customer organizations to resolve technical deployment obstacles and improve Google Cloud.
• Work as a part of a team of Engineers/Consultants that globally ensure 24 hour customer support.
• Understand customer issues, advocate for their needs with internal teams, including Product and Engineering teams, and drive production.
• Work with customers on their production deployment to resolve issues and achieve product readiness and availability.

Minimum qualifications:

• Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
• 5 years of experience with two or more of the following: Web Tech, Data/Big Data, Machine Learning, Systems Admin, Networking, Kubernetes.
• 5 years of experience reading or debugging code in one or more general purpose languages (e.g. Python, Java, Go, C or C++).
• Ability to communicate in Japanese and English fluently to communicate with external and internal stakeholders.

Preferred qualifications:

• Experience with SQL database administration, open source software communities, cloud networking solutions, or distributed computing.
• Experience in data analytics, warehousing, Extract Transform and Load (ETL) development, data science, or other Big Data applications.
• Experience working with recommendation engines, data pipelines, or distributed machine learning.
• Experience working in distributed applications or micro-services in a cloud based environment (e.g., Docker, Kubernetes).
• Experience working in a fluid environment with cross-collaboration across functions.
• Knowledge of Web application development/deployment, HTTP/RESTful API troubleshooting, or database design/troubleshooting.