mateineaga

• Architectured fully configured workflow with goal of deploying applications on Kubernetes cluster across different regions and environments using Flux CD • Integrated automated pull reviews done by AI agents, MCP integration with Confluence for writing documentation based on Terraform modules and with Jira for automating creating new tasks in regard of Secrets Rotation • Reduced 30% manual intervention by fixing existing workflows • Develop and maintain complex CI/CD pipelines in Jenkins, Github Actions for automated build, test, and deployment processes • Got endorsed by the architecture team of the client’s and from the EPAM Management for these implementations and for my overall attitude, being down to tackle new challenges and properly solve them • Reduced uncountable amount of hours by creating automated workflows which are used for patching Kubernetes resources when performing a blue green deployment • Administered and supported Linux-based systems (including SUSE Linux) used in production • Configured Salt Stack formulas in order to achieve a highly automated process of deployment in different scopes: k3s implementation, flux installation, users configured with according permissions • Implemented observability and monitoring solutions using Grafana (LGTM Stack) to improve system visibility and incident response Technologies used: AWS, Microsoft Azure, Kubernetes, Jenkins, Istio, Helm, Groovy, Terraform, Flux CD, GitHub Actions, SUSE Linux, SaltStack, Grafana (LGTM Stack)

Training program conducted by EPAM Systems focused on Cloud and DevOps development. Mastering essentials concepts, including: Docker, Kubernetes, Terraform, AWS, Linux, Scripting: Bash, Version Control with GIT, Python Essentials, Hypervisor Essentials, Networking.

Configured and maintained Azure Data Factory (ADF) pipelines and Databricks workspaces for Data ingestion process • Provisioned and managed multiple virtual machines using Ansible scripts to support distributed data processing workloads • Implemented key features into the Azure cloud environment using Terraform: Document Intelligence, SQL Servers, Databricks Catalogs, Group permissions using Terraform for consistency and repeatability • Designed and built custom containerized GitHub Actions self-hosted runners to support secure and scalable CI/CD executions • Created Network Connectivity Configuration in order to access SQL Server within Databricks clusters • Implemented Azure Resource Health alerts for SQL Servers • Ensured that Databricks catalogs follow proper convention Technologies used: Microsoft Azure, Terraform, Databricks, Azure Data Factory, GitHub Actions