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M Qais
@coretech_001
Software Engineer
Pakistan
Englisch, Urdu
Über mich
I hold a Bachelor's degree in Software Engineering and specialize in DevOps and cloud-native technologies. I have hands-on experience with Docker, Kubernetes, Jenkins, GitHub Actions, Linux, Helm, Argo CD, Prometheus, and Grafana. I have built CI/CD pipelines, containerized applications, automated deployments, and managed Kubernetes workloads. I focus on delivering reliable, scalable, and maintainable solutions with clear communication and timely delivery.
Kompetenzen
M Qais
offline •
Durchschnittliche Antwortzeit: 1 Stunde
Meine Dienstleistungen
Beratung im Bereich Datentechnik
I will install and configure big data applications and tools
DevOps-Containerisierung
I will build, dockerize, and deploy your application on kubernetes
Portfolio
Arbeitserfahrung
DevOps
Aitech Systems • Vollzeit
Jul 2026 - Present • 1 mo
Assisted in building and maintaining CI/CD pipelines using Jenkins and GitHub Actions to automate application build, testing, and deployment. Containerized applications using Docker and Docker Compose to ensure consistent development and deployment environments. Deployed and managed applications on Kubernetes using Deployments, Services, Ingress, ConfigMaps, Secrets, Persistent Volumes, and Network Policies. Created and maintained Helm Charts for reusable and simplified Kubernetes deployments. Implemented GitOps workflows using Argo CD for automated Kubernetes application delivery. Configured monitoring and observability using Prometheus, Grafana, and Loki to monitor application health and collect logs. Worked with Linux systems to troubleshoot deployment issues, optimize infrastructure, and improve application reliability. Collaborated with developers to automate deployment processes and follow DevOps best practices for scalable and reliable software delivery.
Big Data Analyst - Internship
AITeC - National Center for Physics • Vollzeit
Jul 2025 - Oct 2025 • 3 mos
Worked as a Big Data Analyst Intern, focusing on processing and analyzing large-scale datasets to extract meaningful insights. Utilized Apache Spark and Hadoop for distributed data processing and built data pipelines for efficient data ingestion and transformation. Performed data analysis and preprocessing using Python, applying machine learning techniques to identify patterns and trends. Gained hands-on experience with Apache Kafka for real-time data streaming and handling high-throughput data systems. Collaborated with team members to design scalable solutions, optimize query performance, and improve data processing workflows. Delivered insights through reports and visualizations to support data-driven decision-making.
