Satyapramod
Cloud Infrastructure Engineer | DevOps & Automation Specialist
Designing scalable cloud infrastructure using AWS, Azure, automation, and monitoring systems.
About Me
Hello! I'm Satyapramod, a dedicated Cloud Infrastructure Engineer and DevOps Automation Specialist with a passion for building robust, scalable, and efficient cloud environments. My expertise spans across major cloud platforms like AWS and Azure, where I focus on designing, implementing, and optimizing infrastructure for diverse business needs.
With a strong foundation in automation using Python, Bash, and PowerShell, I streamline operations, enhance deployment pipelines, and reduce manual effort. I'm also proficient in setting up comprehensive monitoring and logging solutions, ensuring the high availability and performance of critical systems.
My goal is to leverage cutting-edge cloud technologies and DevOps methodologies to drive innovation and deliver tangible business value.
My Expertise:
- AWS cloud infrastructure
- Microsoft Azure environments
- DevOps practices & CI/CD
- Automation with Python, Bash, PowerShell
- Infrastructure monitoring & logging
- Data visualization & analytics
- System optimization & troubleshooting
Education
Master of Science in Information Technology
Clark University – Worcester, Massachusetts
GPA 3.8
Bachelor of Computer Science
Sharnbasva University – India
Tech Skills
Cloud Platforms
- AWS (EC2, S3, VPC, IAM)
- Azure (VMs, Storage, Networking)
Automation
- Python
- Bash
- PowerShell
DevOps Tools
- Git
- GitHub
- GitLab
- CI/CD
Monitoring
- CloudWatch
- Azure Monitor
Data Analytics
- SQL
- Power BI
- Tableau
Networking
- TCP/IP
- DNS
- VPN
- Firewalls
Security
- IAM
- MFA
- Cloud Security
Virtualization
- VMware
- Hyper-V
Experience
Cloud Infrastructure & Systems Analyst
Path to American Vietnamese Education – Worcester, MA
Apr 2025 – Present- Designed and implemented scalable cloud-based infrastructure solutions using AWS and Azure, ensuring high availability and disaster recovery.
- Automated routine operational workflows and deployments using Python and PowerShell scripting, reducing manual effort by 40%.
- Built interactive dashboards and reports with Power BI and Tableau for infrastructure monitoring and performance analytics.
- Improved operational efficiency by 30% through process optimization and strategic technology integrations.
- Reduced operational costs by 20% by implementing cost-effective cloud resource management strategies and optimizing resource utilization.
- Implemented robust monitoring systems using CloudWatch and Azure Monitor, enabling proactive issue detection and resolution.
Application Support Analyst – Cloud
GoDigit
Jun 2021 – Jun 2023- Provided comprehensive support for applications hosted in AWS and Azure cloud environments, resolving complex technical issues.
- Managed and maintained virtual machines, networking configurations (VPCs, VNETs), and storage solutions across cloud platforms.
- Troubleshot critical IAM (Identity and Access Management) and cloud connectivity issues, ensuring secure and seamless access.
- Monitored system performance, resource utilization, and application health to identify and mitigate potential bottlenecks.
- Developed and implemented automation scripts using Python and Bash for streamlining support operations and incident response.
My Projects
Cloud Infrastructure Deployment
Designed and deployed a highly available, fault-tolerant web application infrastructure on AWS using EC2, S3, RDS, and VPC. Implemented IaC with CloudFormation.
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Automation Framework using Python
Developed a robust Python-based automation framework for managing cloud resources, automating backups, and orchestrating deployment processes across multiple environments.
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Cloud Monitoring Dashboard
Created an interactive monitoring dashboard using Power BI, integrating data from AWS CloudWatch, Azure Monitor, and custom logs for real-time insights into infrastructure health.
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DevOps CI/CD Pipeline
Implemented a fully automated CI/CD pipeline using GitLab CI/CD for a microservices application, including automated testing, building, and deployment to Kubernetes clusters.
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