Cloud Engineer (33-Month Contract), Iits

COMPANY DESCRIPTION Singapore Management University is a place where high-level professionalism blends together with a healthy informality. The 'family-like' atmosphere among the SMU community fosters a culture where employees work, plan, organise and play together - building a strong collegiality and morale within the university. Our commitment to attract and retain talent is ongoing. We offer attractive benefits and welfare, competitive compensation packages, and generous professional development opportunities - all to meet the work-life needs of our staff. No wonder, then, that SMU continues to be given numerous awards and recognition for its human resource excellence. RESPONSIBILITIES This position is for Office of Integrated Information Technology Services (IITS). Infrastructure Management Architect, design, and implement cloud-based solutions that align with both organizational objectives and technical requirements. Collaborate with internal and external stakeholders to seamlessly integrate cloud solutions. Implement Infrastructure as Code (IaC) methodologies to automate and streamline the deployment and management of cloud resources. Continuously optimize cloud infrastructure for performance and cost-efficiency. Monitor and analyze cloud performance, making proactive adjustments as needed. Provide technical expertise on cloud architecture and best practices. Stay abreast of emerging trends and technologies in cloud computing. Recommend appropriate cloud services based on project requirements. Ensure compliance with security standards, regulatory requirements, and best practices in cloud security. Conduct regular security audits and assessments. Manage internal and external stakeholders' relationships Act as a subject matter expert on cloud architecture, participate in technical discussion and provide guidance to stakeholders. Provide training, technical documentation and hands-on support to help teams develop necessary skills and expertise. Develop, maintain, and execute system operation procedures (e.g., IT Disaster Recovery) to improve service availability, reliability, and redundancy. Manage, configure, and maintain HPCC Systems clusters to ensure optimal performance, reliability, and scalability as part of the cloud engineering responsibilities. Consultancy and Support Collaborate with internal and external stakeholders to gain a better understanding of their goals, technical requirements, and current infrastructure. Develop tailored cloud solutions that align with organizational requirements, focusing on scalability, reliability, security, and cost-effectiveness. Provide support to internal stakeholders for cloud data repository and accessing enTRUST. Troubleshoot issues, resolve technical challenges, and deliver ongoing support after project post-implementation. Any other duties assigned. QUALIFICATIONS Bachelor's degree or diploma in Computer Science, Computer Engineering, IT or equivalent with at least 6 years of professional experience in cloud infrastructure engineering. Relevant Cloud platform certifications (e.g. AWS Certified Solution Architect, Azure Solutions Architect Expert) are a plus. HashiCorp Certified Terraform Associate or equivalent Infrastructure-as-Code certification are a plus. Strong communication and stakeholder management skills. Proficiency in Cloud computing concepts, architectures, and service models (IaaS, PaaS, SaaS). Proficiency in Cloud platforms such as AWS, Azure, or Google Cloud Platform, including their services and features. Proficiency in networking fundamentals, including TCP/IP, DNS, VPN, and routing in cloud environments. Proficiency in Cloud security principles, encryption, identity and access management (IAM), and compliance requirements. Proficiency in Cloud platform monitoring, logging, and alerting tools to ensure the performance and reliability of cloud resources. Proficiency in infrastructure provisioning and management tools like Terraform and CloudFormation. Working knowledge of DevOps methodologies, continuous integration/continuous deployment (CI/CD), and automation tools. Working knowledge of containerization technologies such as Docker and container orchestration platforms like Kubernetes. Working knowledge of cloud-based storage solutions, databases, and data analytics platforms. Understanding of data lifecycle management, security, and compliance for sensitive research datasets. Working knowledge of big data platforms (e.g. AWS EMR, Hadoop, Spark)…