Strong understanding and working experience of CI/CD and GitOps
Knowledge of the web services, highly scalable web servers, caching servers, REST and SOAP
Very strong scripting and automation skills including languages such as Python, bash, painless
DevOps engineer with expert knowledge of Elasticsearch platform, experienced in building and managing Elasticsearch clusters (Elasticsearch, Logstash, Kibana) - ideally 5+ years hands on experience
Strong hands-on experience on designing, building and managing scalable, high-performance, distributed enterprise systems
Deployment and configuration of Elastic beats and agents
Management of ingest pipelines and deep understanding of the ingest processors
Working experience in DevOps support model / Tooling Development
Strong understanding in DevOps tools like Azure DevOps
Strong experience in Automation, working knowledge on configuration management tools like Ansible, Chef, Helm
Strong Knowledge on Cloud concepts (Azure) and containerization technologies (AKS)
Working knowledge of Ansible, Terraform, Argo CD
Knowledge on OAuth, SAML concepts
ECK (Elastic Cloud for Kubernetes) experience
ECE (Elastic Cloud Enterprise) experience
Bachelor's degree in computer science, Information Technology, or related field
Excellent communication and interpersonal skills
Ability to work independently and as part of a team in a fast-paced environment
Responsibilities
As a SRE Elasticsearch Automation Engineer, you will be responsible for designing, deploying, and maintaining complex Elastic , Azure infrastructure cloud environment
You will work closely with other infrastructure teams, project managers, to ensure the successful delivery of cloud-based solutions
Designing and implementing ELK (Elasticsearch, Logstash and Kibana) stack solutions
Maintain and Troubleshoot Kubernetes clusters, AKS
Build out CI/CD pipelines (Jenkins, Azure DevOps, ArgoCD) enable self-service build tools and reusable deployment jobs, automate Elasticsearch artefact creation using GitOps
Participate in the analysis and document requirements for development of new or improvement of existing infrastructure automation ("infrastructure as code”) and cloud integration solutions
Implementing a production ready Elasticsearch cluster on on-prem and Kubernetes cluster
Deploying software to new platforms and maintaining multiple environments from Development through Production
Driving enhancements to automated deployment solutions
Working to induce a DevOps mentality and best practices