As a member of this team, you seek out feedback on your designs and ideas and provide the same to others. You constantly ask 'What am I missing?' and 'How will this NOT work'? You don't shy away from what you don't know; you readily admit that you don’t know everything, and use every resource available to learn what you need to know.
Within the Big Data environment, you have a deep understanding of the complex nature of Hadoop. You feel as comfortable building simple data flows as you do digging into Hadoop source code to understand the subtle and obscure problems that can arise in this environment. You work with people, technical and non-technical alike, to understand their Big Data needs and to help them understand what they’re really trying to achieve. You’re a company resource, providing best practices, guidelines, and feedback on internal tools working with Hadoop. You have your finger on the pulse of the cluster, understanding when it’s not working “right” and diving in to diagnose the problem before it becomes systemic.
You have a cool head under pressure. When a technical fire occurs, you understand that putting it out should always avoid collateral damage. When you cause a fire (as everyone inevitably does), you take responsibility for it and work with the team to figure out the right way to put that fire out. You believe blaming is a waste of time: when something goes wrong, you figure out why it happened and how to prevent it from happening again in the future. Better yet, you look for how things went right in the first place and improve upon those.
The design, care, and feeding of our multi-petabyte Big Data environments built upon technologies in the Hadoop Ecosystem
Day-to-day troubleshooting of problems and performance issues in our clusters
Investigate and characterize non-trivial performance issues in various environments
Work with Systems and Network Engineers to evaluate new and different types of hardware to improve performance or capacity
Work with developers to evaluate their Hadoop use cases, provide feedback and design guidance
Work simultaneously on multiple projects competing for your time and understand how to prioritize accordingly
Be part of the On-call Rotation for your areas of responsibility and expertise
Intimate and extensive knowledge of Linux Administration and Engineering.
We use CentOS/Red Hat Enterprise Linux (RHEL), you should too.
Experience in designing, implementing and administering large (200+ node), highly available Hadoop clusters secured with Kerberos, preferably using the Cloudera Hadoop distribution.
In-depth knowledge of capacity planning, management, and troubleshooting for HDFS, YARN/MapReduce, and HBase.
An advanced background with common automation tools such as Puppet.
An advanced background with a higher level scripting language, such as Perl, Python, or Ruby.
Must have experience with monitoring tools used in the Hadoop ecosystem such as Nagios, Cloudera Manager, or Ambari.
Experience with Pepperdata a plus.
Knowledge of Impala and Spark a plus.
Cloudera Certified Administrator for Apache Hadoop (CCAH) a plus
Active member or contributor to open source Apache Hadoop projects a plus.
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