Software Engineer II : Cloudera Object Storage - Powered by Apache Ozone

Cloudera is looking for an exceptional and passionate software engineer 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 ( https://ozone.apache.org ) 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 a Software Engineer II : Cloudera Object Storage - Powered by Apache Ozone, 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). • 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. • Get a unique opportunity to be a part of building a disruptor in the distributed storage space 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 • Relevant industry experience • Strong backend engineering skill set with expertise in Java. Alternatively strong C++ skills with intermediate Java skills. • Hands-on programmer with a good knowledge of data-structures and CS algorithms. • 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 and written communication You may also have: • Experience with large-scale, distributed systems design and development with an understanding of scaling, replication, consistency, and high availability • 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