Senior Engineer, Spark, Open Source, Benchmarks
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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.
Preferred qualifications:
- Experience working with data science tools such as Jupyter notebooks, Open Telemetry, JMX and other monitoring solutions.
- Experience with Database optimizations - query and executor optimizations and Data lakes like Apache Iceberg, Apache Hudi, Delta lake, etc.
- Skills developing highly scalable Cloud or SaaS products.
- Deep expertise with OSS projects like Spark, Hive, Trino and in benchmarking and building custom benchmarks.
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.
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. For engineers passionate about the future of data, you'll be building an AI/ML-ready platform, leveraging native GPU support and specialized runtimes pre-packaged with PyTorch, TensorFlow, and RAPIDS, tightly integrated with Vertex AI for end-to-end MLOps. This is where you architect the unified, open lakehouse of tomorrow, seamlessly connecting with formats like Apache Iceberg, Delta, Hudi and providing enterprise-grade security and scale that empowers the world's most demanding data scientists and engineers.
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.
- Define the roadmap for enhancing open-source technologies like Spark, Hive, Trino, Iceberg, Hudi, and Delta into Dataproc.
- Drive the design and implementation of cutting-edge Data Lakes and Lake Houses, including Apache Iceberg and Hudi along with ehnancing the performance and efficiency of open-source technologies within the platform.
- Develop and implement software solutions leveraging Google technologies for accelerated cluster setup, streamlined operations, and comprehensive monitoring.
- Establish benchmarks to identify and resolve performance bottlenecks, ensuring large-scale Spark job certification.
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