Jobs
Benefits & Perks
•Competitive salary and equity package
•Generous paid time off and holidays
•Flexible work arrangements
•Comprehensive health, dental, and vision insurance
•Parental leave
•Equity
•Flexible Hours
•Healthcare
•Parental Leave
Required Skills
Python
JavaScript
TypeScript
About the job
Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
The Data Center Quality Analytics team delivers automated insights for improving quality and operations in Google’s data centers. We deliver on-demand, custom insights through data engineering, advanced analytics, AI integrations, and custom application development.
The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
The US base salary range for this full-time position is $115,000-$166,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
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Design and implement advanced analytics, AI/ML integrations, and rich data visualizations.
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Own data engineering workstreams, including data acquisition, data pipelining, data quality, data prep, and data warehousing.
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Collaborate with team members in delivering custom web applications.
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Engage stakeholders and partner teams to gain a deep understanding of business needs, and to develop innovative solutions to challenging business problems.
Minimum qualifications
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Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience
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5 years of experience in delivering analytics and data science applications
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5 years of experience in Data Engineering
Preferred qualifications
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Experience with Machine Learning and AI Integrations
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Experience with web development
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About Google

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
63,375 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 / 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
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