Cloud & DevOps Engineer - Kubernetes, CI/CD, AWS/GCP

SHEETAL YADAV

San Jose, CA Open to Relocation

*******.*********@*****.*** +1-408-***-**** linkedin.com/in/sheetalyadav01 github.com/SheetalYadav01 SUMMARY

Cloud and DevOps Engineer with 3 years of experience designing and operating scalable, high-availability distributed systems on AWS and GCP. Specialized in Kubernetes, CI/CD, and production reliability, with proven impact on performance, cost optimization, and scalability. Architected and led cross-cloud platform migration and Kubernetes cluster migration for Mercedes-Benz. Experienced across full SDLC: architecture planning, provisioning, deployment, security, monitoring, and incident response. Hands-on with data-intensive and AI-driven workloads in cloud-native environments. AWS Community Builder. M.S. Computer Software Engineering, SJSU (May 2026). EDUCATION

San José State University, M.S. Computer Software Engineering GPA: 3.8 Aug 2024 – May 2026 Relevant coursework: Cloud Computing, Software Systems Engineering, Machine Learning, Enterprise Distributed Systems, Virtualization University of Mumbai, B.E. Information Technology Jun 2015 – Jun 2019 EXPERIENCE

Infosys Limited Client: Mercedes-Benz Apr 2024 – Aug 2024 Senior Software Engineer - Cloud Infrastructure & DevOps

• Architected and led Kubernetes cluster migration and cross-cloud platform migration for Mercedes-Benz, keeping 15+ production microservices at 99.9% uptime, serving 1M+ daily requests.

• Managed 100+ production releases end to end, coordinating architecture reviews, release planning, and deployment sign-offs across dev, QA, and ops teams, ensuring zero rollbacks and optimizing infrastructure costs.

• Served as primary client contact for Mercedes-Benz, running daily standups and translating business requirements into technical solutions, reducing escalations to senior management by 80%.

• Built Kafka pipeline handling 100K+ daily transactions, onboarded 4 engineers cutting ramp-up time by 50% through structured code reviews and knowledge transfer.

Infosys Limited Client: Mercedes-Benz Apr 2022 – Apr 2024 Software Engineer - Cloud Infrastructure & DevOps

• Built and maintained GitOps CI/CD pipelines using GitHub Actions, ArgoCD, and Bamboo, enabling 100+ zero-downtime deployments across AWS and cutting release cycles from 2 hours to 20 minutes.

• Provisioned multi-cloud infrastructure on AWS and GCP using Python scripts, covering EC2, EKS, VPC, S3, RDS, IAM, and GKE. Managed Kubernetes clusters via Rancher, automating environment setup and cutting provisioning time by 60%.

• Designed and implemented a scalable observability framework using Prometheus and Grafana across 50+ services, improving system reliability and reducing incident detection time by 50%.

• Implemented HashiCorp Vault for secrets management across 20+ services, enforcing zero-trust security across production infrastructure.

• Managed 500GB+ MySQL RDS production database, executing live data queries, bulk data ingestion, and large file uploads via SFTP, ensuring zero data incidents across high-volume production datasets.

• Resolved 150+ critical production incidents with a 15-minute MTTR and 95%+ SLA/SLO adherence via ServiceNow. Automated pod failure detection through scheduled log analysis using cron jobs, enabling proactive issue identification across production Kubernetes workloads. PROJECTS

Cloud-Native Video Streaming Platform CloudFront, Lambda, EC2, S3, RDS, Terraform, Python Jan 2025 – Mar 2025

• Architected a cloud-native AWS app using EC2, S3, RDS, CloudFront, and Lambda, supporting 10K+ concurrent users at 99.9% uptime.

• Provisioned scalable, high-availability infrastructure using Terraform IaC, reducing cloud costs by 35% via Spot Instances for repeatable and controlled deployments.

AI Document Processing Pipeline Python, AWS SageMaker, Comprehend, NLP, Docker, CloudWatch Aug 2024 – Nov 2024

• Designed and deployed an end-to-end ML pipeline on AWS (SageMaker, EKS) for document intelligence, including data processing, model inference, autoscaling, and monitoring in production, improving accuracy by 40%.

• Deployed on EKS with HPA autoscaling achieving sub-200ms inference latency. Monitored with CloudWatch and secured with IAM roles and K8s network policies, optimizing throughput by 60%. SKILLS

Cloud & IaC: AWS (EC2, EKS, VPC, S3, RDS, Lambda, CloudWatch, IAM), GCP (GKE, GCS), Azure, Terraform, Ansible Kubernetes & Containers: Kubernetes (K8s), Docker, Helm, kubectl, HPA, network policies, Rancher CI/CD & GitOps: GitHub Actions, ArgoCD, Bamboo, Jenkins Observability & Security: Prometheus, Grafana, CloudWatch, ELK, SLO/SLA monitoring HashiCorp Vault, IAM Programming & Scripting: Python, Bash/Shell, Java, SQL, YAML Linux (RHEL/Ubuntu), TCP/IP, DNS Databases & Tools: Kafka, MySQL, PostgreSQL, Redis, RDS, SFTP Cron Jobs, Job Scheduling, Automated Workflows Postman, Jira, Confluence, ServiceNow

CERTIFICATIONS AWARDS COMMUNITY

AWS Certified Solutions Architect – Associate AWS Certified Cloud Practitioner AWS Machine Learning Foundations AWS Community Builder AWS re:Invent 2025 Attendee Insta Award, Top 5% of 1,000+ Infosys Engineers GHC 2025 Volunteer AnitaB.org Member Adobe Campus Ambassador

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