Key Responsibilities:

• Expertise in CI/CD tools such as Jenkins, GitLab CI, and Azure DevOps.

• Proficiency in containerization and orchestration tools like Kubernetes and Docker.

• Hands-on experience with scripting languages like Python and Bash for automation.

• Strong knowledge of automation tools like Ansible, Terraform, and similar infrastructure-as-code platforms.

• Experience with cloud platforms like AWS, Azure, or Google Cloud to configure and optimize cloud-native solutions for scalability, performance, and security.

• Knowledge of API management and microservices architectures.

• Experience with data extraction from various sources (e.g., Snowflake, MS SQL, MySQL, M365).

• Knowledge of data visualization tools like Power BI or Qlik Sense.

• Experience with Microsoft Power Platform tools like PowerApps or Power Automate and API management platforms like SnapLogic.

• Familiarity with the concept of ML Ops and data science solutions (e.g., Databricks, AzureML, Cognitive Services, GCP AI Platform).

• Experience in automated testing workflow integration to streamline quality assurance.

• Experience in setting up monitoring solutions to track system performance in real-time and quickly identify and resolve issues to maintain system reliability and availability.

• Knowledge in incident management support, assisting in production issue resolution and restoring service operations.

• Close collaboration with development teams to integrate backend services and ensure alignment between development and production environments.

Preferred Qualifications:

• Certifications in DevOps methodologies (e.g., AWS Certified DevOps Engineer, Azure DevOps Engineer Expert), agile practices, and modern development workflows.

• Proven experience with CI/CD tools, containerization, and cloud infrastructure.

• Strong understanding of network architecture, security protocols, and disaster recovery principles.

• Strong problem-solving skills and attention to detail.

• Experience working in a cross-functional team within an IT organization adopting modular architectures.