Cloudera

Senior Software Engineer - Ozone/HDFS (US/Canada - Remote)

Job Description :

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).

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.

Requirements :

BS, MS, or Ph.D. in Computer Science

Masters +3 years or Bachelors +5 years of 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

Big Pluses :

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

Posted in 2022-08-18

Expired in 2022-11-26

This vacancy has been closed

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