Position: DevOps Engineer
Category: DevOps
English level: intermediate
Years of experience: 1.5

My objective is to work within an IT environment as DevOps Engineer, where I can apply my practical and critical approach with operations, process automatization, continuous integration and continuous delivery.

I’ve built CI/CD pipelines Java C# and Python applications to dev, stage and production environment using GitlabCI, Docker Swarm and Kubernetes from scratch including security testing. 
I’ve written Telegram bot on Python, it notified our team about pipeline status. I’ve written html site using Python and special library for it. 

Areas of Expertise:
• DevOps
• Cloud Infrastructure
• Scripting 
• System & network administration
• IT Security
• Development
Have 1,5 year of experience as DevOps with a tech stack listed below and 7 years in system administering.  Looking for Middle or higher level position.

TECHNOLOGY STACK:
--------------------------------
- Cloud Computing Services: AWS: EC2, IAM, S3, Route 53, RDS, VPC, EKS, Autoscaling, Load Balancing, Lambda
- Orchestration/Containerization/Management: Kubernetes, Docker Swarm, AWS EKS, Helm
- Continuous Integration & Delivery: GitLab CI prefer,  Jenkins 
- Automation & Configuration: Ansible, Terraform, CloudFormation prefer 
- Service Proxy: Nginx Ingress
- Monitoring: Zabbix, AWS Cloud Watch, Prometheus, Grafana, Loki
- Scripting/Programming: BASH, Python 
- Development processes: Python, Java, C#

IT OPERATIONS:
Have 7 years of System & Network Administration. Have built automated CI/CD pipelines from scratch using Gitlab CI technology with static and dynamic automated security testing. Wrote a lot of Dockerfiles using multistage Dockerfiles. Wrote few Telegram bots using Python for CI/CD processes.
I interested to work with:
--------------------------------
Clouds: AWS prefer
Infrastructure as a Code
Microservices: Kubernetes
CI/CD: GitLab CI prefer
Authomation, Scripting
High-load systems
Python
Docker
Prefer a lot of difficult tasks with Kubernetes and AWS