MANTU INTERNATIONAL PTE LTD
Senior DevOps Engineer – Elastic Stack & Kafka
Senior DevOps engineer owning the engineering and operation of production Elastic Stack and Kafka platforms: designing ingestion pipelines, administering Elasticsearch clusters, and automating Linux (RHEL/Ubuntu) operations with Python/Bash, Ansible, and CI/CD while supporting live systems on virtual and physical infrastructure.
- Compensation
- Not disclosed
- Location
- Singapore, Singapore
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Devops
- Posted
Skills
Must have
- Bachelor's degree in Computer Science, IT, Computer Engineering, Systems Engineering, or related technical discipline
- 7+ years of professional experience in platform engineering, DevOps, systems engineering, infrastructure, or related discipline
- At least 4-5 years of direct hands-on experience designing, deploying, and supporting Elastic Stack platforms in production
- Strong production experience with Elastic Stack ingestion, indexing, cluster administration, monitoring, and analytics
- Strong hands-on experience with Kafka in production environments
- Proficient Linux administration skills across RHEL and/or Ubuntu
- At least 2 years of scripting or programming experience using Python or Bash
- Experience with Ansible or a comparable automation and configuration management tool
- Experience with CI/CD pipelines and version-controlled infrastructure or configuration
- Experience supporting live production systems and resolving complex technical incidents
- Experience working with both virtualised and physical infrastructure
- Ability to work independently, manage competing priorities, and take ownership of technical outcomes
Full description
Job description
We’re looking for aSenior DevOps Engineer to own the engineering and operation of production Elastic Stack and Kafka platforms. You’ll design and maintain ingestion pipelines, manage Elasticsearch environments, automate Linux operations, and support live systems across virtual and physical infrastructure. The role requires hands-on engineering, scripting, automation, troubleshooting, and ownership of production outcomes.
ABOUT THE JOB
- Design, deploy, configure, and maintain production Elastic Stack environments.
- Manage Elasticsearch, Kibana, Logstash, Elastic Agent, Beats, and related platform components.
- Build and maintain ingestion pipelines, including parsing, routing, enrichment, indexing, mappings, retention, and data lifecycle policies.
- Manage Elasticsearch cluster health, shard allocation, replicas, storage, capacity, performance, and recovery procedures.
- Operate Kafka environments, including topics, partitions, consumer groups, retention, throughput, consumer lag, and failure recovery.
- Administer and troubleshoot RHEL and Ubuntu servers.
- Investigate indexing failures, ingestion delays, data gaps, cluster issues, performance degradation, and service failures.
- Write automation and operational tooling using Python or Bash.
- Create and maintain Ansible playbooks, roles, and configuration procedures.
- Build and maintain CI/CD pipelines for platform configuration, code, and infrastructure changes.
- Support production environments across virtualised and physical infrastructure.
- Lead incident investigation, root-cause analysis, corrective actions, and technical documentation.
- Work with infrastructure, application, security, and operations teams on platform changes and production support.
ABOUT YOU
- Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, Systems Engineering, or a related technical discipline.
- 7+ years of professional experience in platform engineering, DevOps, systems engineering, infrastructure, or a related discipline.
- At least 4-5 years of direct, hands-on experience designing, deploying, and supporting Elastic Stack platforms in production.
- Strong production experience with Elastic Stack ingestion, indexing, cluster administration, monitoring, and analytics.
- Strong hands-on experience with Kafka in production environments.