Rajesh · Lead Multi-Cloud DevOps Engineer · 10+ yrs
PrincipalAbout Rajesh
Rajesh Kumar Pandey is a seasoned DevOps and Cloud Specialist with nearly a decade of experience in managing cloud environments and implementing automation strategies. He has successfully led various projects that involved migrating on-premises applications to cloud platforms, enhancing operational efficiency, and reducing system downtimes. His expertise spans across AWS, Azure, and GCP, where he has designed and implemented robust CI/CD pipelines and containerization strategies using Docker and Kubernetes. Rajesh is known for his strong ownership of cloud environments and his ability to collaborate effectively with engineering teams.
Core expertise
Additional skills(13)
Azure DevOps
LinuxWhy hire Rajesh?
Managed 100% of existing AWS/Azure Cloud environments
Reduced manual setup time by 60% through automation
Decreased system downtime by 45% for critical applications
Led a team of 6 Engineers in monitoring and alerting systems
Implemented CI/CD pipelines for Django applications
Reduced manual infrastructure setup time by 60% on AWS and GCP using Terraform.
Decreased system downtime for critical applications by 45% through robust monitoring and alerting.
Increased production rates by 20% and reduced machine downtime by 15% through Python-script automation.
Project highlights(6)
MyRewards Portal – DevOps and Cloud Specialist
Overview: This project focused on the complete lifecycle management of a customer rewards portal, including migrating its on-premises infrastructure to the cloud. Responsibilities: Involved in setting up infrastructure and deployment pipelines, designing the overall transformation strategy, and implementing DevOps & DevSecOps practices. Managed 100% of existing AWS/Azure Cloud environments, overseeing automation, monitoring metrics, disaster recovery/backups, and capacity planning.
Key outcomes:
Reduced manual setup time by 60% through automated infrastructure deployment on AWS and GCP using Terraform.
Reduced system downtime for critical applications by 45% by implementing robust monitoring and alerting tools.
Automated CI/CD Pipeline for Django Web Application – DevOps Engineer
Overview: This project involved creating a fully automated CI/CD pipeline for a Django Todo-List web application. Responsibilities: Created the CI/CD Pipeline for a 'Django Todo-List App' from development to deployment. Deployed the project on Amazon AWS EC2 Instance with the help of Docker and Jenkins.
Key outcomes:
Successfully created and deployed a CI/CD pipeline for a Django web application.
Cloud Management & Automation – Cloud Specialist
- This initiative focused on optimizing cloud infrastructure management and automation practices for various systems.
- Key activities included developing proof of concepts, designing technical training, and managing data migration.
- Developed and operated a proof of concept (POC) for IKEA store Cloud/SDN solution integration with SDN and Cloud ecosystems.
- Designed technical training material for internal resources to simplify and scale up their cloud solutions.
- Managed data configuration for migration of traditional infrastructure to cloud-based automated infrastructure.
- Played a key role in architectural discussions to design solutions and ensure successful deployment & security in the cloud.
Key outcomes:
Successfully developed and operated a POC for cloud/SDN solution integration for a major retail client.
Contributed to architectural discussions, ensuring secure and successful cloud deployments.
Managed data configuration for automated cloud migration.
Automating LVM Partition – Software Engineer
- This project involved automating Logical Volume Management (LVM) partition processes to enhance efficiency and reduce manual effort.
- The automation aimed to improve production rates and minimize machine downtime.
- Achieved a 20% increase in production rates by implementing lean manufacturing principles and optimizing workflow processes.
- Reduced machine downtime by 15% through predictive maintenance strategies facilitated by Python-script automation.
Key outcomes:
Increased production rates by 20% through workflow optimization and lean manufacturing principles.
Reduced machine downtime by 15% using predictive maintenance strategies and Python scripting.
AzureDevops Administration Management – Module Lead Engineer
- This role focused on leading a team in managing Azure DevOps environments, encompassing monitoring, administration, and pipeline management across multiple countries.
- The objective was to ensure robust, always-on web environments and continuous process improvement.
- Led a team of 6 Engineers to independently design and manage monitoring and alerting systems across 3+ countries.
- Directed system administration tasks for the Linux environment and deployed software in an always-on web environment.
- Supervised troubleshooting of production issues and updated software patches.
- Ensured pipelines were running smoothly and owned/operated 100% of all configuration and release management governance.
- Automated routine tasks via Shell scripting for boosting personnel productivity & organizational efficiency.
Key outcomes:
Led a team of 6 engineers to manage monitoring and alerting systems across 3+ countries.
Owned and operated 100% of all configuration and release management governance.
Automated routine tasks via Shell scripting to boost personnel productivity and organizational efficiency.
10+ years of industry experience
- •Cloud Management & Automation— Cloud SpecialistSDN · AWS · Azure · GCP
- •Automating LVM Partition— Software EngineerPython
- •AzureDevops Administration Management— Module Lead EngineerAzure DevOps · Linux · Bash
- •Application/FarmersFirst— Senior QAGit
- •MyRewards Portal— DevOps and Cloud SpecialistAWS · Azure · Terraform · Docker +1
- •Cloud Management & Automation— Cloud SpecialistSDN · AWS · Azure · GCP
- •Automating LVM Partition— Software EngineerPython
At a Glance
Single contract. Billed in USD.
Typically responds within 4 business hours.
Top Skills
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Rajesh
DevOps Engineer