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Rahul Sharma

Senior Cloud Engineer AWS Azure IaC & Automation

Cloud Engineer with 5+ years of experience specializing in AWS and hands-on experience across Azure, focused on cloud infrastructure, automation, security, performance, and FinOps. Proficient in Terraform, Python, and Linux, with experience in cloud optimization, production operations, incident management, and troubleshooting.

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RKS

Available for opportunities

5+

Years Exp.

20+

Accounts Reviewed & Managed

2×

Awards

Experience

CloudThat Technologies Pvt. Ltd.

Oct 2024
Aug 2026

Senior Research Associate

Conducted Well-Architected reviews of 10+ AWS accounts, achieving a 25% reduction in costs and improving security through IAM policy remediation and resolving GuardDuty and Trusted Advisor findings.
Automated scheduling of EC2 instances, RDS database backups, S3 object replication, and EKS cluster scaling with Python, Boto3, AWS Lambda, and Terraform, reducing manual effort by 80%.
Configured and maintained Azure DevOps CI/CD pipelines to automate infrastructure and application deployments across client environments, improving release consistency and reducing manual deployment steps.
Automated CI/CD workflows using AWS CodePipeline and CodeBuild, integrating source control, automated builds, testing, and deployments to improve release consistency and reduce manual deployment effort.
Designed and executed Azure tenant-to-tenant migrations with under 2 hours of downtime, ensuring the integrity of the migrated data and the compliance of the migrated tenant to regulatory requirements.
Implemented least-privilege IAM/RBAC controls across AWS/Azure environments to reduce excessive permissions and strengthen access governance.
Automated IAM hygiene reviews across multiple AWS Organization accounts to identify inactive users, unused access keys, and excessive permissions, and handled access provisioning and role creation based on the findings.
Hardened Azure VM access by disabling SSH and moving to username/password authentication with monthly rotation, integrating AWS Secrets Manager to automate the rotation and distribution of credentials. Configured read-only Secrets Manager access so users can retrieve current passwords without being able to modify them, eliminating manual password handoffs after each rotation.
Mentored junior engineers and interns in various aspects of cloud computing, including AWS/Azure fundamentals, Infrastructure-as-Code practices and incident response processes to accelerate their ramp-up to client-facing work.
Queried logs stored in Amazon S3 using AWS Athena to perform security verification and operational audits.

Nov 2021
Sep 2024

Research Associate

Provided cloud cost analyses for clients using AWS and Azure platforms, resulting in 20%+ monthly savings for clients after implementing recommendations from tools like Cost Explorer, Trusted Advisor, Compute Optimizer, and Azure Cost Management.
Built and maintained Terraform Infrastructure-as-Code templates for repeatable, compliant environment provisioning.
Deployed Azure VM Scale Sets (VMSS) behind a Standard Load Balancer across multiple availability zones for health-routed high availability and performed rolling upgrades of VM images without disrupting application services.
Automated S3 data workflows, billing alerts and internal logistics pipelines using Python and AWS Lambda, cutting process times by 60%.
Automated the lifecycle management of EC2 and RDS instances using Lambda functions to handle instance start/stop scheduling and used Data Lifecycle Manager to manage database snapshots - supporting a 99.9% uptime SLA.
Implemented an end-to-end Amazon Pinpoint integration to reach customers through scalable, targeted multichannel communications, storing delivery logs in S3 and analyzing engagement metrics using an AWS Glue job to extract email addresses from the SES suppression list.
Set up parallel staging environments that mirror the production environment to validate the deployment of the application prior to rollout in production.

Apr 2021
Oct 2021

Research Intern

Built and deployed a highly available Moodle LMS on AWS, resulting in a 75% reduction in application downtime compared to the existing environment.
Implemented basic DevOps pipelines, containerized application components using Docker, and automated operational workflows using Azure Logic Apps.