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Big Data Administration

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Job Description

·         Deploying a Hadoop cluster, maintaining a Hadoop cluster, adding and removing nodes using cluster monitoring tools like Ganglia Nagios or Cloudera manager, configuring the NameNode high availability and keeping a track of all the running Hadoop jobs.
·         Implementing, managing and administering the overall Hadoop infrastructure with various distributions (Cloudera, Hortonworks or IBM BigInsights)
·         Takes care of the day-to-day running of Hadoop clusters
·         Participate in the architectural discussions, perform system analysis which involves a review of the existing systems and operating methodologies.
·        Participate in the analysis of latest technologies and suggest the optimal solutions which will be best suited for satisfying the current requirements and will simplify the future modifications
·         Design and Build the necessary infrastructure for optimal ETL from a variety of data sources
·         Collaborate with the business to scope requirements. Key Skills/Experience
·         5 + years of Data Engineering experience working with both distributed architectures, ETL, EDW, and Big Data technologies
·         Extensive experience working with SQL across a variety of databases
·         Experience working with both structured and unstructured data sources.
·         Experience with NoSQL databases, such as HBase, Cassandra, MongoDB or similar
·         Experience with Big Data tools such as Pig, Hive, Impala, Sqoop, Kafka, Flume, Jupiter
·         Experience with Hadoop, HDFS, Spark, Informatica BDM
·         Experience in Linux administration, Unix Shell Scripts
·         Person will be responsible to Perform Hadoop Administration on Production/DR Hadoop clusters.
·         Perform Tuning and Increase Operational efficiency on a continuous basis
·         Monitor health of the platforms and Generate Performance Reports and Monitor and provide continuous improvements
·         Working closely with development, engineering and operation teams, jointly work on key deliverables ensuring production scalability and stability
·         Develop and enhance platform best practices
·         Ensure the Hadoop platform can effectively meet performance & SLA requirements
·         Responsible for support of Hadoop Production environment which includes Hive, Ranger, Kerberos, YARN, Spark, SAS, Kafka, base, etc.
·         Perform optimization, capacity planning of a large multi-tenant cluster.
·         Identify, Implement and continuously enhance the data automation process

If you''re interested in this role, please send your resumes to #removed#

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