Senior Software Engineer, Google Cloud Storage

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience programming in C++, Java or Python.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.

Preferred qualifications:

• Experience in distributed systems and storage systems.

About the job

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.

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.

Responsibilities

• Design, code, and test improvements across the GCS client stack.
• Take ownership of new features from concept to launch by writing scalable code, authoring comprehensive design documents, and providing critical feedback in design reviews to influence technical direction.
• Systematize benchmark GCS client performance for critical AI/ML and workloads. Use profiling and analysis to identify bottlenecks and implement optimizations that deliver measurable gains in throughput and latency.
• Take an active role in debugging complex, real-world customer issues. Analyze client-side behavior, trace problems through the stack, and implement code changes in our SDKs and connectors to resolve them, directly improving customer satisfaction.
• Enhance the telemetry and observability of our clients by adding structured logging and metrics that make it faster to diagnose future customer issues and understand performance characteristics in production environments.