Minimum qualifications:- Bachelor's degree in Computer Science, Data Science, Statistics, Information Systems, Business Analysis, Business Administration or a related field and 6 years of progressive, post-baccalaureate experience in the job offered or in a Web Solutions Engineering-related occupation.
- Alternatively, will accept a Master's degree in Computer Science, Data Science, Statistics, Information Systems, Business Analysis, Business Administration or a related field, and 4 years of experience in the job offered or in a Web Solutions Engineering-related occupation.
- Position requires 4 years of experience in the following: Backend development using Java, Python, or C ; Creating UIs with TypeScript and Angular; Designing robust database schemas for large scale applications; Designing and documenting robust and scalable systems, applying architectural patterns; and System issue diagnosis and root cause analysis.
About the jobThe US base salary range for this full-time position is $174,650 - $224,000 15% bonus target equity benefits determined by role, level, and location. Individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Learn more about benefits at Google .
Position reports to the Google San Bruno, CA office & may allow for a hybrid schedule as per Google policy.
Responsibilities- Drive feature changes by analyzing large datasets on user behaviors to identify high-impact improvement opportunities.
- Optimize front-end code and tools while conducting peer reviews to ensure technical accuracy and alignment with user needs.
- Collaborate with product managers and business leaders to define requirements and prioritize new web features.
- Establish engineering standards and complete documentation regarding application architecture, design steps, and integration processes.
- Guide engineering teams through the full development lifecycle including prototyping, testing, and risk evaluation. Define technical solutions for disaster recovery, data integrity, and security to maintain resilient data infrastructures.
