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.
As a member of the YouTube Ads Data Infrastructure team, you will design and scale the critical data systems that power everything from ads model training and analytics to billing and reporting. You will have an opportunity to gain a deep understanding of the YouTube Ads stack while collaborating with various product teams to engineer the data infrastructure of the future.
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 $207,000-$300,000 + 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
- Drive execution of high-impact, visible data projects, establishing the technical strategy and investment road-map for sustainable YouTube Ads growth.
- Architect cost-efficient, sub-linear data and logging infrastructure capable of managing millions of Queries Per Second (QPS) for model training, billing, and reporting.
- Deliver critical data solutions, including low-latency streaming datasets and improving end-to-end log freshness from over 40 hours to under 6 hours.
- Collaborate with executive leaders and product teams across the organization to unify workflows, ensure compliance, and maximize Return on Investment (ROI).
- Guide and mentor team engineers while directly contributing to technical design, coding, and solving ambiguous, complex technical problems.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience programming in C++.
- 3 years of experience with software design and architecture.
- 5 years of experience building and developing large-scale infrastructure and large-scale distributed systems.
- Experience with storage systems.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- Experience in people management.
- Experience in data analytics, preferably with Google analytics.
- Experience working with compute infrastructure.