Elastic Stack Platform Engineer - Automation & Production

ARGYLL SCOTT CONSULTING PTE. LTD.

Singapore

On-site

SGD 120,000 - 180,000

Full time

3 days ago
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Job summary

ARGYLL SCOTT CONSULTING PTE. LTD. is seeking an Elastic Stack Engineer in Singapore.

The role is 12 months (extendable), start ASAP, with 4+ years of hands‑on experience and strong background in Elastic Stack, Kafka, Linux administration, scripting, and automation. You will manage large-scale production platforms, ensure reliability, performance, and scalability, and contribute to automation and DevOps practices.

Qualifications

  • Candidates must have extensive hands‑on experience with Elastic Stack components (Elasticsearch, Logstash, Kibana) and production-grade deployments.
  • Strong experience in Kafka, Linux administration, scripting, and automation is required.
  • 7+ years of professional experience with 4–5+ years in Elastic Stack platform design, deployment, and production support.

Responsibilities

  • Manage and support production-grade Elastic Stack environments (ingestion, indexing, monitoring, analytics).
  • Design and implement automation to improve reliability, efficiency, and scalability.
  • Provide hands-on Linux administration across RHEL and Ubuntu.
  • Manage Kafka environments and integrations.
  • Develop scripts in Python and/or Bash; build automation with Ansible or similar tools.
  • Support CI/CD pipelines and DevOps practices; perform production troubleshooting and RCA.

Skills

Elastic Stack - Mandatory
Elastic Search
Logstash
Kibana
Indexing & analytics
Monitoring
Kafka
Linux Administration
RHEL
Ubuntu
Programming / Scripting
Python
Bash
Automation & DevOps
Ansible
CI/CD
Infrastructure automation

Tools

Ansible

Job description

ARGYLL SCOTT CONSULTING PTE. LTD. is seeking an Elastic Stack Engineer in Singapore.

The role is 12 months (extendable), start ASAP, with 4+ years of hands‑on experience and strong background in Elastic Stack, Kafka, Linux administration, scripting, and automation. You will manage large-scale production platforms, ensure reliability, performance, and scalability, and contribute to automation and DevOps practices.

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