Hadoop Administrator

at Apex Systems Inc

location Cincinnati, Ohio

Updated on Aug 11, 2017

Contract Position
6 month(s)

  • Referral Bonus

    $532

    approx.
  • Signing Bonus

    $532

    approx.

Pay Rate $53.20 per hour

Experience 7-12 Years

Eligibility H-1B visa, Green Card, US citizen

Industry

Information Technology Services

Travel

Not Specified

Job ID

PARDC13800

Working Remotely Allowed

No

JOB DESCRIPTION

Face to face interview required.

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 Apache Spark/Scala

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