Staff Software Engineer - Ozone
Business Area: Engineering Seniority Level: Mid-Senior level Job Description: At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises. The Data Platform Pillar is the bedrock of Cloudera’s technology, where we design and build the core components that let our customers store, manage, and process data with unmatched scalability, security, and performance. Cloudera is looking for an exceptional and passionate software engineer with a distributed systems background to join the Storage Engineering team focused on building Apache Ozone. The Storage team is responsible for the primary storage and storage access layers which are core to the Cloudera Data Platform. Apache Ozone ( is an open source project purposed to build a massively scalable distributed object store. Ozone is designed to scale to thousands of nodes, tens of billions of objects and overcome the limitations of the Hadoop Distributed File System (HDFS). As the Staff Software Engineer you will: You will be directly involved in the design and implementation of the core feature set of Apache Ozone and Apache Ratis (open-source RAFT implementation). You will also contribute to HDFS; the development of HDFS which is one of the most widely deployed distributed storage systems in the world with over a thousand Cloudera customers. This is a unique opportunity to be a part of building a brand new distributed storage system and have a huge impact on the big data and cloud computing industry. We’re excited about you if you have: BS, MS, or Ph.D. in Computer Science OR Masters or Bachelors +6 years of relevant industry experience Strong backend engineering skill set with expertise in Java. Hands-on programmer with a good knowledge of data-structures and CS algorithms. Experience with large-scale, distributed systems design and development with a strong understanding of scaling, replication, consistency, and high availability Experience with system software design and development with an understanding of computer architecture, storage, network, and IO subsystems Clean coding habits, attention to detail, and focus on quality Good oral, written and communication skills. You may also have: Background in a distributed storage system including file systems, database storage internals, no-sql storage or distributed hash tables Background in performance tuning, identifying performance bottlenecks, and implementing performance optimizations Good understanding of Apache Hadoop Recognized contributions to open source projects Experience using projects in the Apache Hadoop ecosystem such as MapReduce, HBase, Hive, Spark etc. is a big plus Understanding of Paxos, RAFT, or equivalent distributed consensus protocols. Why this role matters: You will tackle complex distributed systems challenges, crafting the foundational software for the control and data planes that powers CDP and keeps it running at massive scale. Working at the forefront of hybrid and multi-cloud technology, you will empower data scientists, engineers, and analysts with the tools and infrastructure they need for advanced analytics and modeling. Collaboration is key, you will work alongside brilliant minds across product, data science, and engineering to drive innovation, standardize best practices, and shape the future of enterprise AI and data platforms. This is your chance to build the future of data and see your work make a global impact. What you can expect from us: Generous PTO Policy Support work life balance with Unplugged Days Flexible WFH Policy Mental & Physical Wellness programs Phone and Internet Reimbursement program Access to Continued Career Development Comprehensive Benefits and Competitive Packages Paid Volunteer Time Employee Resource Groups EEO/VEVRAA #LI-REMOTE #LI-SZ1