Site Reliability Engineer III (Data Platform)

Location: Kuala Lumpur, Malaysia

Company

hirify.global provides a cloud platform for property and casualty insurers, combining digital, core, analytics, and AI capabilities.

What you will do

• Operate and enhance production data platform services to maintain high availability, performance, and cost efficiency.
• Manage and optimize Kafka, Hadoop, Spark, and Hive platforms on AWS, including configuration, tuning, and daily operations.
• Define SLOs, error budgets, capacity plans, and scaling strategies for data platform components.
• Participate in on-call rotations, triage alerts with PagerDuty, resolve production incidents, and contribute to blameless post-incident reviews.
• Build automation and troubleshooting tools with Go, Python, or scripting, and support CI/CD pipelines with TeamCity or GitHub Actions.
• Maintain infrastructure with Terraform or AWS CloudFormation, operate Kubernetes environments on AWS EKS, and implement blue/green and canary deployments.

Requirements

• 4–6 years of experience in Site Reliability Engineering, DevOps, Production Engineering, or similar roles supporting distributed systems or data platforms.
• Experience deploying and operating services on AWS or Azure, including on-call support.
• Expertise with Kafka, Hadoop, Spark, or Hive, plus proficiency in Go, Python, or Bash.
• Experience with CI/CD, Infrastructure as Code, Kubernetes, Docker, observability, and logging tools.
• Understanding of distributed systems, networking, storage, operating systems, and incident response.
• Bachelor’s or master’s degree in Computer Science, Computer Engineering, Mathematics, or a related technical field, or equivalent practical experience.

Nice to have

• Knowledge of Java and Spring Boot.
• Familiarity with Kubevela or Crossplane.
• Kubernetes or AWS certifications.
• Contributions to open source projects.

Culture & Benefits

• Collaboration with product engineering, data platform, and security teams.
• Agile practices including Scrum and Kanban.
• Blameless incident reviews focused on reliability improvements, runbooks, and automation.
• Work supporting AI, cloud, analytics, and data platform adoption.