채용
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 mission of the Data Center Quality Engineering team is to identify and resolve product and process issues in the DC to ensure high quality deployments and reliable hardware that meet Google Cloud’s Time To Market (TTM) need. We exist in the data center to gather data, find root cause, and collaborate to create solutions that make our partner teams successful.
The US base salary range for this full-time position is $171,000-$248,000 + 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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Provide expert-level technical direction for quality engineering, defining the goal across global regions and multiple data center product lines.
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Lead high-performing teams to optimize DC workflows, enhancing the speed and reliability of hardware deployments while eliminating systemic inefficiencies.
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Formalize feedback loops between field observations and product design to mitigate recurring hardware issues and evolve damage control programs.
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Own complex root cause analyses for critical, ambiguous technical issues, ensuring robust product quality and predictable fleet-wide deployment.
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Translate complex performance data and risk assessments into actionable strategic roadmaps and investment justifications for Director and VP-level leadership.
Minimum qualifications
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Bachelor's degree in Electrical Engineering, Mechanical Engineering, Computer Science or a related technical field equivalent practical experience.
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10 years of experience in hardware quality engineering, manufacturing operations, or hyperscale data center environments.
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3 years of experience managing technical teams of engineers or technicians in infrastructure.
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Experience using structured Root Cause Analysis (RCA) methodologies (e.g., 8D or 5-Why) to resolve hardware failures.
Preferred qualifications
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Proficiency in quality improvement frameworks like Six Sigma, Lean, or ISO 9001 to manage hardware lifecycle standards.
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10 years of experience in data center infrastructure or operation.
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Experience leading cross-functional problem-solving teams using practical approaches.
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Track record of coaching and mentoring technical teams, fostering a culture of continuous learning and data-driven decision-making.
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Ability to communicate complex technical findings into actionable executive summaries for cross-functional leadership and partner teams.
총 조회수
0
총 지원 클릭 수
0
모의 지원자 수
0
스크랩
0
비슷한 채용공고
Google 소개

Google specializes in internet-related services and products, including search, advertising, and software.
10,001+
직원 수
Mountain View
본사 위치
$1,700B
기업 가치
리뷰
3.7
25개 리뷰
워라밸
3.8
보상
4.2
문화
3.4
커리어
3.9
경영진
2.8
68%
친구에게 추천
장점
Excellent compensation and benefits
Smart and talented colleagues
Great perks and work flexibility
단점
Management and leadership issues
Bureaucracy and slow processes
Constantly changing priorities and reorganizations
연봉 정보
57,502개 데이터
Junior/L3
L3
L4
L5
L6
L7
L8
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Junior/L3 · Data Scientist L3
0개 리포트
$176,704
총 연봉
기본급
-
주식
-
보너스
-
$150,298
$203,110
면접 경험
9개 면접
난이도
3.4
/ 5
소요 기간
14-28주
합격률
44%
경험
긍정 0%
보통 56%
부정 44%
면접 과정
1
Application Review
2
Online Assessment/Technical Screen
3
Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
자주 나오는 질문
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Product Sense
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