Cloudera Hadoop Admin

Ness Digital EngineeringBengaluru, KarnatakaOn-siteFull-timeMid level, 2–5 yearsListed 5 hours ago

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About this role

Cloudera Hadoop Admin JD:

- 5+ years in Hadoop administration
- Strong experience in administration of large & complex Cloudera Hadoop environments
- Certification in Cloudera Hadoop administration
- Strong performance optimization skills with large Hadoop clusters
- Experience in On-call support (after hours), coordination with L1 teams / remote support teams
- Experience in issue escalation and resolution working with vendor support (Cloudera)

Key activities include:

- Monitoring and Administration activities of the Cloudera platform​

- Install and deploy the Hadoop cluster, add and remove nodes​
- Configure name-node, take backups, patch installations etc.​

- Monitor tasks and all the critical parts of the cluster​
- Maintenance and Operational activities​
- Maintenance of file system/log files.​
- Manage OS Patching, cluster parcels updates.

- Disaster recovery: Backup plan for accidental data deletion.​
- Continual improvement: Performance optimization, automation and improvements
- Code deployments in Production environment
- ## Mandatory Skills
5+ years of Hadoop Administration experience in enterprise environments.
- Strong hands-on experience with Hadoop, HDFS, YARN, Hive, Spark, Kafka, ZooKeeper, and Oozie .
- Expertise in Linux/Unix administration , shell scripting, and system troubleshooting.
- Experience with Hadoop cluster installation, configuration, monitoring, performance tuning, and capacity planning.
- Knowledge of Hadoop security including Kerberos, Ranger, LDAP/Active Directory integration .
- Experience with backup and recovery, high availability, and disaster recovery processes.
- Familiarity with monitoring tools such as Ambari, Cloudera Manager, Grafana, Splunk, or equivalent .
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication and stakeholder management skills.

Preferred Skills

- Experience with Cloudera CDP, Hortonworks, or MapR .
- Exposure to cloud-based big data platforms such as Azure HDInsight, Azure Databricks, AWS EMR, or Google Dataproc .
- Python automation and Infrastructure-as-Code experience.
- Basic understanding of SQL and data warehousing concepts.