Cloud Administrator

Nityo Infotech; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

An established industry player is seeking a Senior Technical Resource Specialist to manage and optimize big data platforms. In this dynamic role, you will be responsible for the installation and maintenance of Hadoop clusters, ensuring high availability, and implementing security measures. You'll also monitor system performance, automate workflows, and collaborate with data engineers to support ETL pipelines. If you thrive in high-pressure environments and are passionate about big data technologies, this is the perfect opportunity to advance your career in a supportive and innovative setting.

Qualifications

• Strong knowledge of big data ecosystems and Linux/Unix administration.
• Experience with monitoring tools and scripting skills.

Responsibilities

• Install and maintain big data platforms and ensure high availability.
• Monitor performance and optimize cluster utilization.

Skills

Big Data Ecosystems (Hadoop, HDFS, YARN, Hive, HBase, Spark, Kafka, Elastic Search)

Linux/Unix System Administration

Monitoring Tools (Nagios, Grafana, Splunk, HPOMI)

Scripting (Python, Ansible, Shell, Bash)

Cloud Platforms (AWS, Azure, GCP)

Problem-Solving

Communication Skills

Time Management

Tools

Apache Oozie

Apache Airflow

Ambari

Cloudera Manager

Prometheus

Job description

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Senior Technical Resource Specialist At Nityo Infotech

Main responsibilities for this Role

1. Cluster Setup and Maintenance:
   • Install, configure, and maintain big data platforms like Hadoop Clusters, Elastic Search, Spark, Kafka, Hive etc.
   • Set up and manage distributed file systems (HDFS) and NoSQL databases (HBase, Cassandra).
   • Ensuring high availability and reliability of Hadoop, Kafka and Elasticsearch Clusters.
2. Performance Optimization:
   • Monitor system performance, fine-tune jobs, and optimize cluster utilization.
   • Manage and resolve performance bottlenecks in big data environments.
3. Security Management:
   • Implement data security policies, user authentication (Kerberos), and access control (Ranger, Knox).
   • Regularly review and plan patch systems to ensure data integrity.
   • Apply updates, patches, and version upgrades to all managed systems.
   • Ensuring the backward compatibility and minimal downtime during upgrades.
   • Troubleshoot and fix the issue based on pre-defined SLA.
   • Restore the services in case of system/service downtime based on the SLA.
   • Provide timely update to the users on the situation.
   • Escalate to management based on escalation matrix.
4. Capacity Management:
   • Monitor the utilization of the data platform and plan for any expansions if required.
5. Backup and Recovery:
   • Plan and implement backup and recovery strategies for big data environments.
   • Develop disaster recovery solutions and test failover scenarios.
6. Workflow Automation:
   • Design and implement workflows using tools like Apache Oozie or Apache Airflow.
   • Automate cluster management tasks like upgrades and scaling.
   • Developing shell scripts and Ansible Playbooks to automate routine tasks, including monitoring, backups, and deployments.
7. Monitoring and Support:
   • Monitor logs, metrics, and system health using tools like Ambari, Cloudera Manager, or Prometheus.
   • Provide 24/7 on-call support for production systems and resolve incidents.
8. Data Security and Privacy:
   • Implement data security measures to safeguard sensitive information within the data environments.
   • Ensure compliance with data privacy regulations and industry standards.
9. User Access Management:
   • Onboard and offboard users to the platform based on the approval sought.
   • Conduct regular review of user accounts and take necessary actions to ensure users are valid and active.
   • Provision user access based on the approval.
   • Preparing access control report across the env’s and upload to COSMOS portal.
10. Work closely with data engineers and developers to support ETL pipelines and data processing jobs.
11. Collaborate with stakeholders to ensure big data systems meet organizational needs.
12. Working transversally with other teams to guarantee high data quality and availability.
13. Cloud migration:
    • Experience in Migrating from On-premises to GCP & AWS cloud.

Work Schedule

1. Work schedule is mainly focused to support Asia and EMEA (Paris) time zone; however, may have to support during non-office hours for critical incidents or escalation as per the assigned on-call support requirements.
2. Rotational Shift schedule is followed.

Work Hours: 9:30 AM – 6:30 PM SGT (with 1 week of Paris shift 2 PM – 11 PM SGT).

Qualification and Profile

1. Technical Skills:
   • Strong knowledge of big data ecosystems (Hadoop, HDFS, YARN, Hive, HBase, Spark, Kafka and Elastic Search).
   • Proficiency in Linux/Unix system administration.
   • Experience with monitoring tools like Nagios, Grafana, or Splunk, HPOMI.
   • Scripting skills in Python, Ansible, Shell, or Bash.
   • Familiarity with cloud platforms (AWS, Azure, GCP) and their big data services.
2. Soft Skills:
   • Strong problem-solving and analytical abilities.
   • Effective communication and collaboration skills.
   • Ability to handle high-pressure production environments.
   • Ability to organize and prioritize work as per the Operation’s needs.
   • Should have time management skills and able to manage work in fast moving environment.
   • Excellent written and oral English language skills; knowledge of French language is good to have.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Information Technology

Industries

Information Services