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Consulting/Contract
UG :- - Not Required
PG :- - Not Required
No of position :- ( 1 )
Post :- 22nd Jan 2023
Atleast 5 years of production experience of Hadoop Platform Administration (Capacity Planning, Optimization, Troubleshootin, Administration with Ambari Experience.
Primary responsibility would be to test the cluster setup and configuration changes and troubleshooting of platform related issues. Spark on Kubernetes would be leveraged, and other technology replacement service migration needs to be tested. A custom UI been developed for Cluster Management for Visa.
• Person will be responsible to Perform Big Data Platform Administration and Engineering activities on multiple Hadoop, Kafka, Hbase and Spark clusters
• Work on Performance 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 Big Data Production environment which includes Hadoop (HDFS and YARN), Hive, Spark, Livy, SOLR, Oozie, Kafka, Airflow, Nifi, Hbase etc
• Perform optimization, debugging and capacity planning of a Big Data cluster
• Perform security remediation, automation and selfheal as per the requirement
• Hands on Experience in Hadoop Admin, Hive, Spark, Kafka, experience in maintaining, optimization, issue resolution of Big Data large scale clusters, supporting Business users and Batch process.
• Hands-on Experience No SQL Databases HBASE is plus
• Prior Experience in Linux / Unix OS Services, Administration, Shell, awk scripting is a plus
• Excellent oral and written communication, analytical and problem-solving skills
• Self-driven, Ability to work independently and as part of a team with proven track record
• Experience on Hortonworks distribution or Open Source preferred.