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

Google

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

Google

·

On-site

·

Full-time

·

1w ago

About the job

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. Big Query), 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. This may include a need to sometimes work non-standard work hours or shifts.

  • 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.

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About Google

Google

Google

Public

Google specializes in internet-related services and products, including search, advertising, and software.

10,001+

Employees

Mountain View

Headquarters

$1,700B

Valuation

Reviews

3.7

25 reviews

Work-life balance

3.8

Compensation

4.2

Culture

3.4

Career

3.9

Management

2.8

68%

Recommend to a friend

Pros

Excellent compensation and benefits

Smart and talented colleagues

Great perks and work flexibility

Cons

Management and leadership issues

Bureaucracy and slow processes

Constantly changing priorities and reorganizations

Salary Ranges

57,502 data points

Junior/L3

L3

L4

L5

L6

L7

L8

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L3

0 reports

$176,704

total per year

Base

-

Stock

-

Bonus

-

$150,298

$203,110

Interview experience

9 interviews

Difficulty

3.4

/ 5

Duration

14-28 weeks

Offer rate

44%

Experience

Positive 0%

Neutral 56%

Negative 44%

Interview process

1

Application Review

2

Online Assessment/Technical Screen

3

Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

Common questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Product Sense