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Staff Software Engineer, Infrastructure, Google Cloud

Google
Bengaluru, IND
Senior · 8+ years experience
Onsite
Discovered 3 days ago
javajavascriptpython

Full Job Posting

Responsibilities

  • Design and develop systems or enhancements to existing telemetry, monitoring, and logging infrastructure to improve observability and debugging for Dataproc and Managed Service for Apache Spark.
  • Architect and optimize observability pipelines for Spark Streaming and Structured Streaming workloads, providing insights into micro-batch latencies, checkpointing bottlenecks, and input message lag.
  • Apply Apache Spark core internals knowledge to build tools that detect performance regressions, data skew, and resource inefficiencies in customer workloads.
  • Collaborate with cross-functional partners (e.g., Product, UX) to design and deliver intuitive monitoring dashboards, cost-attribution features, and developer tools.
  • Collaborate with Dataproc and Cloud Platform teams to integrate and release telemetry features, OpenTelemetry (OTel) pipelines, and diagnostic frameworks safely at scale. Build robust monitoring systems providing visibility, execution history, and real-time performance insights into distributed big data workloads.

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 8 years of experience programming in C++, Python, C, C++, Java and JavaScript.
  • 5 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
  • 5 years of experience testing, and launching software products.

Preferred qualifications:

  • 8 years of experience with data structures and algorithms.
  • 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 with a backend server infrastructure.
  • Understanding of algorithms and data structures, and their time and space performance.

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