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Building reliable
cloud infrastructure
I design, automate, and scale production cloud systems across AWS, Azure, and GCP for enterprise and Fortune 500 teams. Security and observability go in from day one, not bolted on after the fact.
About
Who I am
I'm a Cloud & DevOps Engineer who turns manual, fragile infrastructure into systems that are secure, automated, and easy to observe. I care about things that hold up under real production load, not just in a demo.
Across AWS, Azure, and GCP, I've standardized 300+ CI/CD pipelines for a HIPAA-regulated healthcare enterprise, kept a Fortune 500 energy client's infrastructure online through 50+ monthly production incidents, and built Terraform-driven cloud benchmarking platforms for research at the University of Arizona.
What excites me most:
Master of Science
Management Information Systems
University of Arizona · 2024 – 2025
Bachelor of Technology
Electronics & Telecommunication Engineering
University of Mumbai · 2018 – 2022
Open to roles in
Experience
Where I've worked
Cloud Support Engineer
McKeever Lab, University of Arizona
- Engineered an automated cloud benchmarking platform with Terraform, provisioning reproducible Hadoop/Spark environments on Azure to evaluate runtime, resource utilization, reliability, and cost
- Built a performance optimization engine that analyzes workload and infrastructure metrics to predict execution time, flag resource bottlenecks, and recommend cost-efficient cluster configurations
DevOps Engineer Intern
Blue Cross Blue Shield of Arizona
- Standardized 300+ CI/CD pipelines across 5 teams by integrating automated SAST/DAST scanning through SonarQube and Veracode, advancing HIPAA-compliant release practices
- Built PowerShell automation identifying 70+ inactive Azure DevOps users across license tiers, replacing manual account reviews and surfacing roughly $30K in potential annual licensing savings
- Implemented automated smoke tests and REST API validation checks with email notifications, establishing automated quality gating for critical API pipelines
Cloud Engineer
LTIMindtree
- Engineered Python and AWS Lambda automation across infrastructure provisioning, resource management, monitoring, and optimization, reducing repetitive operational work for cloud infrastructure teams
- Built Ansible playbooks and Terraform modules to provision and configure Azure infrastructure, cutting manual environment setup time by over 80%
- Owned 24/7 production reliability for a Fortune 500 energy client, resolving 50+ monthly production incidents through Azure troubleshooting and root-cause remediation
Data Analyst Intern
MEDTOUREASY
- Built automated reporting dashboards with Power BI and SQL Server, reducing manual reporting by 50%
- Designed data pipelines for healthcare analytics supporting 10,000+ patient records
Projects
What I've built
NYC Taxi Dynamic Fare Estimation Platform
Real-time fare estimation requires scalable infrastructure, low-latency APIs, and reliable deployments. Manual deployments and lack of automated testing led to frequent downtime.
- Containerized the ML model and API using Docker for consistent environments
- Built GitHub Actions CI/CD pipeline with automated linting, testing, and deployment
- Implemented Redis caching layer reducing API response time by 60%
- Configured environment separation (dev/staging/prod) with managed PostgreSQL
YouTube Trends Analytics Pipeline
Processing large-scale YouTube data required serverless architecture that handles variable workloads without over-provisioning. Traditional ETL pipelines were too rigid and expensive at scale.
- Built event-driven data pipeline using AWS Lambda triggered by S3 uploads
- Automated data cataloging with AWS Glue crawlers for schema discovery
- Enabled ad-hoc SQL queries on S3 data lake using Athena (no database provisioning)
- Implemented cost optimization with S3 lifecycle policies and intelligent tiering
Bakery Demand Forecasting System
Small businesses struggle to plan seasonal production from historical sales data. This project packages demand forecasting as a cloud service so forecasts can be generated through an API instead of spreadsheets.
- Built a containerized forecasting service using Python and Prophet
- Deployed on DigitalOcean App Platform with autoscaling containers for inference
- Used object storage for model artifacts and scheduled batch retraining via cron
- Exposed forecasts through an HTTPS-secured REST API
Philosophy
How I work
Automation-First
If you're doing it manually more than twice, it should be automated. I treat infrastructure as code and deployment as a product feature — it's how I cut manual environment setup time by over 80% at LTIMindtree.
Security by Default
Security isn't a checkbox — it's integrated into the pipeline. I've standardized SAST/DAST scanning across 300+ pipelines in a HIPAA-regulated environment without slowing teams down.
Observability as a Feature
You can't improve what you can't measure. Monitoring, logging, and alerting are core infrastructure — not afterthoughts bolted on after an incident.
Infrastructure as Product
Platform teams exist to enable developers, not gatekeep. I design self-service infrastructure — golden templates, clear docs, safe rollback paths — that's easy to adopt and hard to misuse.
Skills
Technical toolkit
Cloud Platforms
AWS
Azure
GCP
Multi-cloud infrastructure design and migration experience
Infrastructure & Automation
IaC
CI/CD
Containers
GitOps workflows and immutable infrastructure patterns
Observability & Security
Monitoring
Logging
Security
Shift-left security and compliance automation
Programming & Data
Languages
Databases
Analytics
Infrastructure automation and data pipeline development
Certifications
Credentials
HashiCorp Certified: Terraform Associate (004)
HashiCorp
Microsoft Certified: Azure Administrator Associate
Microsoft
Microsoft Certified: Azure Fundamentals
Microsoft
Microsoft Certified: Power BI Data Analyst Associate
Microsoft
Microsoft Certified: Azure Data Fundamentals
Microsoft
Microsoft 365 Fundamentals
Microsoft
HackerRank SQL (Intermediate)
HackerRank
Contact
Let's build something
reliable together
I'm actively seeking Cloud, DevOps, Platform Engineering, or SRE-focused roles — open to relocation anywhere in the US. Let's connect and discuss how I can help your team build resilient, scalable systems.