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.

Spanner combines the power and familiarity of relational databases with horizontal scalability typical of non-relational stores. It is the first scalable, enterprise grade, globally distributed, and strongly consistent database service.

The Spanner Analytics team's mission is to unify transactional and analytical workloads to allow real-time insights and serving of operational and lakehouse data. We work closely with internal and external customers to ensure analytic queries scale and perform on exabytes of data.

As a Senior Software Engineer, you will help extend and build out the federated query capabilities of Spanner so that it scales to the growing needs of our most demanding customers inside and outside Google.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

The US base salary range for this full-time position is $174,000-$252,000 + 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

• Deliver features end-to-end across the Google Cloud Platform (GCP) tech stack.

• Analyze CPU and latency performance to identify bottlenecks and estimate beneficial impact.

• Propose technical solutions and help build consensus on technical strategy.

• Drive the rollout to production.

• Propose solutions and detailed designs, help drive consensus on the right trade-offs, write well-optimized C++ code, and land your optimizations in Google-internal and Cloud production environments.

Minimum qualifications

• Bachelor’s degree or equivalent practical experience.

• 5 years of experience with software development in one or more programming languages.

• 3 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.

• Experience programming in C++

• Experience with cloud, databases, performance optimization, and benchmarking.

Preferred qualifications

• Master's degree or PhD in Computer Science, or a related technical field.

• 5 years of experience with data structures and algorithms.

• Experience in one or more of the following: data analytics, apache iceberg, distributed databases, SQL, data warehousing, database internals.

• Experience building transaction processing systems (Online Transactional Processing (OLTP)) or large-scale analytics (Online Analytical Processing (OLAP)).

• Experience building data warehousing systems (e.g., Spark, Big Query etc.).

• Experience architecting and developing large-scale distributed systems.