Educational Requirements

Bachelor of Engineering

Service Line

Data Analytics Unit

Responsibilities

- Install, configure, administer, and maintain Hadoop clusters in production environments.
- Manage and support Hadoop ecosystem components such as HDFS, YARN, MapReduce, Hive, HBase, Spark, Sqoop, Oozie, Kafka, ZooKeeper, and Impala.
- Perform cluster monitoring, health checks, capacity planning, and resource optimization.
- Configure and manage Hadoop security including Kerberos, Ranger, Knox, and LDAP/AD integration.
- Troubleshoot cluster, application, and performance-related issues.
- Plan and execute Hadoop upgrades, patches, and migrations with minimal downtime.
- Implement backup, recovery, and disaster recovery procedures.
- Monitor system performance using tools such as Ambari, Cloudera Manager, Grafana, Nagios, or Prometheus.
- Support data engineering and analytics teams in deploying and troubleshooting workloads.
- Manage user access, permissions, and governance policies.
- Automate administrative tasks using Shell Scripting, Python, or Ansible.
- Ensure platform compliance with organizational security and operational standards.
- Create and maintain operational documentation,



runbooks, and SOPs.

Technical and Professional Requirements:
- Solid experience in Hadoop Administration (Apache Hadoop, Cloudera CDP/CDH, Hortonworks HDP, or MapR).
- Hands-on experience with HDFS, YARN, Hive, Spark, HBase, Kafka, and ZooKeeper.
- Experience with Linux/Unix administration.
- Proficiency in Shell Scripting and basic Python scripting.
- Knowledge of Hadoop cluster architecture, resource management, and performance tuning.
- Experience in troubleshooting distributed systems and production support environments.
- Understanding of high availability, disaster recovery, and backup strategies.
- Experience with security tools such as Kerberos, Ranger, Knox, and LDAP.
- Cloud platform exposure (AWS EMR, Azure HDInsight, Databricks, or GCP Dataproc).
- Knowledge of containerization technologies like Docker and Kubernetes.
- Experience with CI/CD and automation tools such as Jenkins and Ansible.
- Understanding of data warehousing and ETL concepts.

Preferred Skills:
- Technology->Big Data - Hadoop->Hadoop Administration

📌 Hadoop Admin (Hyderabad)
🏢 Infosys
📍 Hyderabad