Senior Software Engineer, Dataproc

1 week ago


Bengaluru, Karnataka, India Google Full time ₹ 20,00,000 - ₹ 25,00,000 per year
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 testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  • 3 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
Preferred qualifications:
  • Master's degree or PhD in Computer Science or a related technical field.
  • 5 years of experience with data structures/algorithms.
  • Experience with Open Telemetry, JMX and other monitoring solutions.
  • Experience working with data science tools such as Jupyter notebooks.
  • Experience with Database optimizations such as query and executor optimizations and data lakes like Apache Iceberg, Apache Hudi, Delta lake, etc.
  • Expertise in OSS projects like Spark, Hive, Trino, etc.
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.

Google Cloud Dataproc is a fully managed service for running open-source data processing frameworks such as Apache Spark, Hadoop, Flink, Trino and more on Google Cloud. It simplifies the deployment, scaling, and management of big data clusters, allowing users to focus on analytics and data science instead of infrastructure.

Join the Google Cloud Dataproc team and become a pioneer in the next generation of data processing, combining the best of open source with Google's planetary-scale innovation. We're not just managing Apache Spark and Hadoop clusters; we're fundamentally accelerating big data with breakthroughs like the Lightning Engine, a new proprietary execution layer delivering up to 4.3x faster query performance and massive cost savings without code changes.

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:
  • Lead the development of next-generation features, positioning Cloud Dataproc as the preferred platform for Spark, Flink, Trino, and emerging cloud technologies.
  • Drive the design and implementation of data lakes and lake houses, including Apache Iceberg and Hudi.
  • Define the roadmap for enhancing open-source technologies like Spark, Hive, Trino, Iceberg, Hudi, and Delta into Dataproc.
  • Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
  • Develop and implement software solutions leveraging Google technologies for accelerated cluster setup, streamlined operations, and comprehensive monitoring. Position Cloud Dataproc as the optimal choice for data science, machine learning, and artificial intelligence workloads.


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