DevOps Engineer - Terraform / Docker / Kubernetes

We are seeking a highly motivated and experienced DevOps Engineer to join our growing team.

As a DevOps Engineer, you will play a crucial role in designing, implementing, and maintaining our cloud infrastructure and CI / CD pipelines, with a focus on AWS cloud technologies, big data solutions, and Jenkins automation.

You will work closely with development and operations teams to ensure smooth and efficient software delivery, scalability, and reliability with a strong emphasis on security best practices.

Responsibilities :

• Design, implement, and manage AWS cloud infrastructure using services like EC2 S3 VPC, IAM, Lambda, ECS, EKS, EMR and AWS Backup.
• Implement and manage infrastructure as code (IaC) using tools like Terraform or CloudFormation.
• Optimise cloud costs and performance.
• Ensure high availability and disaster recovery for cloud resources.
• Implement robust backup and recovery strategies using AWS Backup.
• Design, implement, and maintain CI / CD pipelines using Jenkins.
• Automate build, test, and deployment processes.
• Integrate various DevOps tools into the pipeline (e. g., code analysis, security scanning, artefact repositories).
• Implement and manage containerization technologies like Docker and Kubernetes.
• Implement and enforce security best practices across all infrastructure and applications.
• Configure security groups, network ACLs, and IAM roles to control access to resources.
• Implement security monitoring and alerting to detect and respond to threats.
• Ensure compliance with security standards and regulations.
• Integrate security tools and services into the CI / CD pipeline.
• Implement monitoring and logging solutions to track system health, performance, and security.
• Utilise tools like CloudWatch, Prometheus, Grafana, and ELK stack.
• Analyse logs and metrics to identify and resolve issues proactively.
• Work closely with development and operations teams to ensure seamless software delivery.
• Participate in agile development processes and sprint planning.
• Clearly communicate technical solutions and challenges to stakeholders.
• Design and implement data pipelines for ingestion, processing, and storage of large datasets using EMR clusters.
• Optimise big data infrastructure for performance and scalability, including tuning EMR clusters and Spark applications.

Requirements :

(ref : hirist.tech)