Job Description :
Hadoop Administrator
Interview process: Phone, Skype and F2F
Duration: till Jan 2018
Location: Cincinnati, OH
Need Local for In Person Interview
Need a consultant with great communication skills as well
Position Description:
Hadoop Administrator on a team that supports Cloudera based Hadoop cluster
Position/Project Specific Requirements:
Technical Responsibilities:
The design, care, and feeding of 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
Responsible for ongoing administration of Hadoop infrastructure.
Work with data delivery teams to setup new Hadoop users. This job includes setting up Linux users, setting up Kerberos principals and testing HDFS, Hive, Pig and
MapReduce access for the new users.
Performance tuning of Hadoop clusters and Hadoop MapReduce routines
Manage and monitor Hadoop connectivity, performance, security, log files
HDFS support and maintenance, capacity planning
Collaborating with application teams to install operating system and Hadoop updates, patches, version upgrades when required.
Required Skills:
Experience with Cloudera
Experience Hadoop system administration including HDFS, Yarn, MapReduce, Hive, Pig, HBase
In depth knowledge of configuration, capacity planning and tuning of services such as MapReduce, Hive, Yarn, HBase
In depth knowledge of HDFS file formats such as ORC, Avro, Parquet and others
Experience with data ingestion and streaming frameworks such as Sqoop, Flume, Kafka
General operational expertise and excellent troubleshooting skills, understanding of system capacity, bottlenecks, basics of memory, CPU, OS, storage, and networks
Experience with Kerberos (security)
Position/Project Specific Preferences/Desires:
Pluses:
SQL and HiveQL knowledge
Oozie Workflow scheduler system
Experience with Python
Experience with Spark