Staff Software Engineer

An NYSE-listed company allowing consumers to rapidly convert complicated data into relevant and actionable insights is looking for a Staff Software Engineer. The chosen candidate will contribute to the development of Hadoop Distributed File System (HDFS), one of the world's most commonly used distributed storage systems. The company's hybrid data platform for modern data architectures allows users to leverage both private and public cloud advantages. The company has managed to raise around $1bn in funding so far. 

Job Responsibilities:

• Take part in the design and implementation of Apache Ozone and Apache Ratis' primary feature set
• Participate in the development of a fresh new distributed storage system that will have a significant influence on the big data and cloud computing industries
• Work with large-scale, distributed systems design and development
• Develop scalable components for maximum performance across a vast array of devices and web browsers

Job Requirements:

• Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
• At least 9+ years of relevant experience as a software engineer
• Strong back-end engineering skill set with expertise in Java
• Familiarity with C++ and intermediate Java skills
• Knowledge of data structures and CS algorithms
• Strong understanding of scaling, replication, consistency, and high availability
• Knowledge of 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 English communication skills
• Background in a distributed storage system, including file systems, database storage internals, no-SQL storage, or distributed hash tables, is nice to have
• Background in performance tuning, identifying performance bottlenecks, and implementing performance optimizations is a plus
• Recognized contributions to open source projects is nice to have
• Experience using projects in the Apache Hadoop ecosystem such as MapReduce, HBase, Hive, Spark, etc. is highly desirable
• Understanding of Paxos, RAFT, or equivalent distributed consensus protocols is nice to have