Senior Software Engineer, Full Stack, Google Ads User Objectives id-7344
Job Description
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
- 3 years of experience with full stack development, across back-end such as Java, Python, GO, or C codebases, and front-end experience including JavaScript or TypeScript, HTML, CSS or equivalent.
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
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Preferred qualifications:
- Master's degree or PhD in Computer Science, or a related technical field.
- 1 year of experience in a technical leadership role.
- Experience developing accessible technologies.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
In this role, you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions. You will lead the development of goals features in Google Ads front-end stack. You will operate with autonomy on a platform that interacts with numerous advertising systems, providing an environment to solve ambiguous problems at scale and influence the product/technical direction. You will be responsible for solving problems, and delivering quality user experiences.
Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We're made up of multiple teams, building Google's Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.
The US base salary range for this full-time position is $166,000-$244,000 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
- Write and test product or system development code.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Drive front-end by establishing best practices and design patterns, improving code quality and maintainability, and mentoring engineers.
- Collaborate cross-functionally with Product Management, UX, Research, and other Engineering teams to align direction and deliver advertiser solutions.
- Analyze experiment results and usage data to understand feature impact, identify opportunities, and inform future development.
