Cloud DevOps Engineer with 3+ Years Experience

Sathvika Varala Cloud DevOps Engineer

KS, USA +1-913-***-**** ***********@*****.*** LinkedIn SUMMARY

Cloud DevOps Engineer with 3+ years of experience managing and automating cloud infrastructure across AWS, Azure, and GCP. Skilled in CI/CD pipelines, Docker, Kubernetes, Helm, and infrastructure as code using Terraform, CloudFormation, and ARM Templates. Experienced in monitoring, logging, and security with Prometheus, Grafana, ELK Stack, CloudWatch, and IAM, improving uptime, deployment reliability, and operational efficiency.

TECHNICAL SKILLS

Cloud Platforms: AWS (EC2, S3, Lambda, RDS, VPC, IAM), Azure (VMs, Blob Storage, Azure Functions), GCP (Compute Engine, Cloud Storage) Infrastructure as Code (IaC): Terraform, AWS CloudFormation, Ansible, ARM Templates CI/CD & Automation: Jenkins, GitHub Actions, GitLab CI/CD, CircleCI, ArgoCD, Spinnaker Containerization & Orchestration: Docker, Kubernetes, OpenShift, ECS, EKS, Helm Scripting & Programming: Bash, Python, PowerShell, Groovy Monitoring & Logging: Prometheus, Grafana, ELK Stack, CloudWatch, Azure Monitor, Splunk, Nagios Version Control & Collaboration: Git, GitHub, GitLab, Bitbucket, Jira, Confluence Networking & Security: TCP/IP, DNS, HTTP, VPNs, Load Balancers, Firewalls, SSL/TLS, IAM, Security Groups Databases & Storage: MySQL, PostgreSQL, MongoDB, DynamoDB, S3, Azure Blob, EBS DevOps & Security Practices: Blue/Green Deployments, Canary Releases, DevSecOps, SAST/DAST, Policy-as-Code PROFESSIONAL EXPERIENCE

Marriott International, USA Sep 2024 - Current

Cloud DevOps Engineer

Planned and executed CI/CD pipelines using Jenkins, GitHub Actions, and Terraform across AWS and Azure, reducing deployment time by 40% while ensuring reliable, automated infrastructure provisioning for enterprise applications.

Managed containerized workloads with Docker, Kubernetes, and Helm, achieving 99.9% uptime, optimizing multi-region resource utilization, reducing cloud operational costs by 25%, and improving overall deployment efficiency across all production systems.

Developed monitoring and alerting solutions with Prometheus, Grafana, ELK Stack, and CloudWatch, detecting system anomalies proactively, reducing incident response time by 30%, and improving operational observability for multiple enterprise applications.

Applied cloud security compliance using IAM, Security Groups, and DevSecOps practices, integrating automated SAST/DAST scanning, reducing vulnerabilities by 35%, and ensuring adherence to organizational and regulatory security standards.

Optimized multi-region cloud deployments, improving resource utilization by 20%, reducing latency, and enhancing performance for enterprise applications across AWS and Azure while supporting scalability and high availability objectives.

Collaborated with development and QA teams to reduce release failures by 30%, improving software delivery success rate, maintaining production stability, and enhancing reliability during high-volume enterprise deployments. Intel, India Jun 2021 - Dec 2022

Cloud DevOps Engineer

Automated AWS and Azure cloud infrastructure provisioning using Terraform, CloudFormation, and Ansible, reducing manual errors by 50% and improving deployment reliability and consistency across multiple enterprise environments.

Built and maintained CI/CD pipelines using GitLab CI/CD and ArgoCD, implementing blue/green and canary deployments, reducing release cycles by 35%, and ensuring zero downtime during production releases.

Managed Docker, Kubernetes, and OpenShift containerized applications, improving cluster scalability by 40%, optimizing resource allocation, and enhancing high availability and performance for enterprise workloads across multiple cloud environments.

Enforced monitoring and logging with Grafana, Prometheus, and CloudWatch, analyzing system metrics, reducing mean time to recovery by 25%, and improving operational efficiency and application stability across production systems.

Reduced cloud operational costs by 20% through automated scaling policies, resource optimization, and workload management, maintaining efficient utilization while supporting high availability for containerized enterprise applications.

Conducted security audits and mechanized automated DevSecOps scanning, reducing vulnerabilities by 30%, ensuring compliance with enterprise standards, and strengthening cloud infrastructure security posture across all deployed environments. Intel, India Dec 2020 - May 2021

Cloud Engineer

Built automated cloud infrastructure templates using ARM, Terraform, and CloudFormation, improving provisioning speed by 30%, reducing manual errors, and enabling consistent deployments across AWS, Azure, and GCP environments.

Supported Jenkins and GitHub Actions CI/CD pipelines, streamlining deployment processes, maintaining environment consistency, and accelerating enterprise software delivery across multi-cloud infrastructure environments.

Assisted with Docker and Kubernetes containerization and orchestration, optimizing multi-environment deployments, improving resource utilization, and enhancing reliability and performance of production cloud workloads.

Systematized monitoring and security solutions using CloudWatch, Azure Monitor, Nagios, and IAM, reducing downtime, improving uptime by 15%, and ensuring compliance with organizational cloud infrastructure security standards. EDUCATION

Masters in Computer Science Jan 2023 - May 2024

University of Central Missouri Warrensburg, Missouri, USA Bachelor of Technology in Computer Science Aug 2018 - Jun 2022 BVRIT Hyderabad College of Engineering for Women, Hyderabad, India COURSEWORK

Cloud Computing - Virtualization, cloud services (AWS, Azure, GCP), distributed systems Advanced Operating Systems - Linux administration, process management, containerization concepts Advanced Software Engineering - Agile methodologies, CI/CD pipelines, version control CERTIFICATIONS & TRAINING

Python for AI/ML - Talent Sprint (Scripting & automation for DevOps pipelines) Java Fundamentals - Oracle Academy (Programming foundation for microservices & automation) IoT Foundation - NASSCOM / Jigsaw Academy (Cloud integration & automation concepts) PROJECTS

Brain tumor detection

Developed and containerized a robust CNN model for brain tumor detection using TensorFlow, Python, and Docker, enabling scalable deployment on cloud platforms (AWS/GCP/Azure).

Implemented CI/CD pipelines for automated model training, validation, and deployment, leveraging cloud GPUs to optimize performance and reduce deployment time.

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