Hardware Data and Failure Analysis Engineer

Google; Mountain View (CA); On-site; USD 132,000 - 190,000; Full time

Job summary

Google is seeking a Hardware Data and Failure Analysis Engineer in Mountain View, CA to drive reliability for consumer electronics. You will work with product management and design teams to define tests and oversee failure analysis, using statistics and data analytics to inform robust designs.

You will bridge labs and field data, applying ME/EE/Materials knowledge with data pipelines to uncover root causes and recommend corrective actions for future products.

Qualifications

• Bachelor's degree in Hardware Engineering or equivalent practical experience.
• 4 years of experience analyzing hardware performance, manufacturing, or lab test data.
• Experience investigating technical anomalies or field failures, finding root causes, and documenting corrective actions.
• Experience designing, debugging, or performing failure analysis on hardware.
• Experience applying statistical methods, data modeling (e.g., regression), or machine learning to solve physical engineering problems.
• Experience in technical communication, including simplifying data into concise messages.

Responsibilities

• Navigate and synthesize product datasets (telemetry, reliability results, failure analysis, field returns, customer sentiment) to identify and motivate areas for product improvement.
• Identify true root causes by leveraging all available data sources, including direct FA, and referring to cross-product and generation-over-generation information. Distill findings into a clear problem statement.
• Collaborate with cross-functional teams to develop mitigation strategies, and identify pathways to validate these strategies.
• Recommend and drive corrective action to improve future products.
• Develop software, AI skills, and processes to automate and accelerate future workstreams.

Skills

Data analysis

Failure analysis

Statistics

Machine learning

Technical communication

Regression modeling

Education

Bachelor's degree in Hardware Engineering

Master's or PhD in EE/CE/Physics

Tools

Python

SQL

JMP

Weibull++

Job description

Hardware Data and Failure Analysis Engineer

Mountain View, CA, USA

Mid

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

Minimum qualifications:

• Bachelor's degree in Hardware Engineering or equivalent practical experience.
• 4 years of experience analyzing hardware performance, manufacturing, or lab test data.
• Experience investigating technical anomalies or field failures, finding root causes, and documenting corrective actions.
• Experience designing, debugging, or performing failure analysis on hardware.
• Experience applying statistical methods, data modeling (e.g., regression), or machine learning to solve physical engineering problems.
• Experience in technical communication, including simplifying data into concise messages.

Preferred qualifications:

• Master's or PhD degree in Electrical Engineering, Computer Engineering, Physics, or a related field.
• ASQ certification (CRE, CQE, etc.)
• Experience with AI: utilizing agent harnesses, version control of skills, etc.
• Experience working at multiple stages in the product life cycle.
• Knowledge of Python, SQL, JMP, Weibull++ or similar tools for data analysis and visualization.
• Track record of working across disciplines such as bridging the gap between direct lab environments and data analytics pipelines.

About the job

As a Reliability Engineer, you will play a key role in creating new consumer electronic products that meet a high bar for reliability and performance. You will work closely with the product management and design engineering teams to define standards, specify tests, and then supervise test execution and failure analysis. A broad engineering background and command of statistical methods will help to inform design of new products. Your strong interpersonal and communication skills will be key to ensuring adoption of your technical recommendations.

We are looking for a curious, cross-functional problem solver to help us understand exactly how our products perform in the real world. In this role, you will be the bridge between our labs and the field using both direct forensic analysis mechanical engineering/electrical engineering (ME/EE/Materials) and data analytics to uncover the story behind issues.

You won’t just find the root cause; you will collaborate directly with design and manufacturing teams to turn those insights into future-proof solutions. You will grow on cross-functional teamwork to directly shape next-generation products.

Google's mission is to organize the world's information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user's interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people's lives better through technology.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $132000 - $190000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Navigate and synthesize product datasets (telemetry, reliability results, failure analysis (FA), field returns, customer sentiment, etc.) to identify and motivate areas for product improvement.
• Identify true root causes by leveraging all available data sources, including direct FA, and referring to cross-product and generation-over-generation information. Distill findings into a clear problem statement.
• Collaborate with cross-functional teams to develop mitigation strategies, and identify pathways to validate these strategies.
• Recommend and drive corrective action to improve future products.
• Develop software, AI skills, and processes to automate and accelerate future workstreams.

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Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

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