Cloudera Migration Specialist (On-prem To Azure)

10 - 12 years

0 - 1 Lacs

Posted:1 day ago| Platform: Naukri logo

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Work Mode

Hybrid

Job Type

Full Time

Job Description

Experience Required:

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Work Type

Job Summary:

Key Responsibilities:

  • Lead and execute the migration of Cloudera workloads (HDFS, Hive, Spark, Impala, HBase, etc.) from on-premise infrastructure to Azure.• Assess the existing Cloudera cluster, identify dependencies, and prepare a detailed migration roadmap.• Develop and implement data migration scripts, workflows, and cloud-native configurations.• Design and deploy equivalent services on Azure using Azure HDInsight, Azure Data Lake, Azure Synapse, or other relevant services.• Ensure data integrity, performance tuning, and post-migration validation.• Collaborate with infrastructure, security, and DevOps teams to ensure compliance and automation.• Prepare and maintain documentation of the migration plan, architecture, and troubleshooting playbooks.• Provide knowledge transfer and training to internal teams post-migration.

    Required Skills & Experience:

  • 3–4 years of hands-on experience with Cloudera (CDH/CDP) ecosystem components (e.g., HDFS, YARN, Hive, Spark, Impala, HBase).• Proven experience in Cloudera cluster migrations, preferably to cloud platforms like Azure.• Solid understanding of cloud-native equivalents and data architectures on Azure.• Experience with Azure services such as HDInsight, Data Lake Storage, Synapse Analytics, Blob Storage.• Proficiency in Linux system administration, shell scripting, and automation tools.• Strong problem-solving and troubleshooting abilities in distributed data environments.• Familiarity with security controls, Kerberos, Ranger, LDAP integration, and data governance

    Preferred Qualifications:

  • Cloudera Certified Administrator / Developer.
    • Experience with Azure DevOps, Terraform, or Ansible for infrastructure provisioning.• Knowledge of disaster recovery planning and HA architectures on Azure.• Familiarity with performance tuning in cloud vs. on-prem Hadoop environments

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