Three main job tittle description & requirement with Hadoop Big data

Hadoop Administrator
  • Job description
    •  Work as a Systems Administrator who have responsibilities include setting up, backup, monitor, recovery and maintenance Hadoop clusters.
  • Skills Required
    • Good knowledge of hardware systems
    • able to work with cloud computing environments;
    • Scripting skills in Linux environment: Linux shell, python, ruby, perl, ..
    • Experience in Fail over, High avaibility, Load balancing, Replication, System performance turning
    • Monitor tools: Nagios, Ganglia, Munin, Cacti
    • Configuration management tools: Puppet, Chef, Salt Stack, Ansible, ...
    • Understanding of Hadoop architecture


Hadoop Developer
  • Job description
    • Work as a developer in big data domain wh responsible for the actual coding/programming of Hadoop applications or other same project. Ideally the candidate should have at least 2 years of experience as a programmer.
  • Skills Required
    • Experience in Fail over, High avaibility, Load balancing, Replication, Application performance turning
    • Experience with strong oop, multi threading language with huge data processing library like Java, Python,  ...
    • Ability to write MapReduce jobs 
    • Experience in interacting with Hdfs, Pig, Hive, ...
    • Familiarity with data loading tools like Flume, Scribe, Kafka, Sqoop
    • Knowledge of workflow/schedulers like Oozie


Hadoop Architect
  • Job description
    • A Hadoop architect is responsible for planning and designing next-generation "big-data" system architectures, also responsible for managing the development and deployment of Hadoop applications.
  • Skills Required
    • Experience in Fail over, High avaibility, Load balancing, Replication, System performance turning
    • Planning for system scale up and scale out
    • Able to help program and project managers in the design, planning and governance of implementing projects of any kind;
    • Exprience with Hadoop Distribution: Cloudera, Hortonwork, Mapr, ...
    • Designing efficient and robust ETL workflows;
    • Extensive knowledge about Hadoop Architecture and HDFS
    • Hands on experience in other Hadoop sub projects: Mapreudce, Hdfs, Hbase, Oozie, Hive, Pig, ...