You will work closely with development teams to ensure efficient and reliable software delivery, as well as identify and implement improvements to our systems and processes.
RESPONSIBILITIES
Design, implement, and maintain highly available and scalable infrastructure on cloud platforms such as AWS, Azure, or GCP.
Build and maintain deployment pipelines
Design and implement data pipelines to support various data processing needs across the organization.
Work closely with development teams to ensure code is deployed efficiently and reliably while maintaining high standards of security and performance.
Identify and implement improvements to our systems and processes, including automation and monitoring solutions.
Troubleshoot and resolve issues related to infrastructure and deployments.
Collaborate with cross-functional teams to ensure seamless integration of new features and technologies.
4+ years of experience in DevOps, Site Reliability Engineering, or a related field.
Strong experience in designing, implementing, and maintaining infrastructure on cloud platforms such as AWS, Azure, or GCP.
Proven Experience with both Docker and Kubernetes.
Strong scripting skills using languages such as Python and Bash.
Experience using and building deployment pipeline tools such as Azure DevOps, GitHub Actions, GitLab CI/CD, Jenkins, or CircleCI.
Problem-solving skills and ability to identify, explain, and troubleshoot complex issues.
Excellent communication and collaboration skills, with a proven ability to work effectively in a team environment.
Bachelors or masters degree in computer science, Engineering, or a related field.
BSc/MSc in Information Management, Mathematics, Statistics, Computer Science, or related fields.
ADVANTAGE
Experience with C# and their build and deployment process in both Windows and Linux environments.
Experience with monitoring and logging tools such as ELK stack, Prometheus, or Grafana.
Experience with database systems such as MySQL, PostgreSQL, or MongoDB.
Experience with Machine Learning tools and methodologies, including deployment, monitoring, construction of training pipelines and experiment tracking.
