Senior Software Engineer, Full Stack, Google Cloud

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 full stack development, across back-end such as Java, Python, Golang, 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.
• 1 year of experience with software design and architecture.

Preferred qualifications:

• Master's degree or PhD in Computer Science or a related technical field.
• 5 years of experience with data structures and algorithms.
• 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.

Responsibilities

• Design and develop systems or enhancements to existing telemetry, monitoring, and logging infrastructure to increase observability and debugging capabilities for Dataproc and Managed Service for Apache Spark.
• Architect observability pipelines specifically for Spark Streaming and Structured Streaming workloads, providing customers with actionable insights into micro-batch latencies, checkpointing bottlenecks, and input message lag.
• Apply deep knowledge of Apache Spark core internals and execution engines to build tools that automatically detect performance regressions, data skew, and resource inefficiencies in customer workloads.
• Collaborate with cross-functional partners to design and deliver intuitive monitoring dashboards, cost-attribution features, and developer experience tools.
• Collaborate with Dataproc and Cloud Platform Software Engineers and SRE teams to integrate and release telemetry features, OpenTelemetry pipelines, and diagnostic frameworks safely at scale, providing visibility, execution history, and real-time performance insights into distributed big data workloads.