Shrivallabh Mahajan

Technical Leader with 11+ years of experience in building and scaling cloud-native applications and platforms. Proven expertise in delivering enterprise-grade solutions that drive business value.

Strong background in Python development and application architecture, with hands-on experience across AWS and Azure to design secure, reliable, and cost-efficient systems.

Hands-on leader in DevOps and automation, leveraging Kubernetes, Terraform, CI/CD pipelines, and modern observability tools to accelerate delivery and ensure operational excellence.

Engineering & Product Development Leadership

• Led cross-functional teams of developers and automation engineers to design and deliver scalable infrastructure automation platforms using Python (Flask), Terraform, and Ansible.
• Spearheaded the modernization of legacy monolithic systems into microservice-based, cloud-native architectures leveraging Docker and Kubernetes (EKS/AKS).
• Partnered with global product and architecture teams to implement Agile-based SDLC practices, ensuring secure, iterative, and business-aligned software delivery.
• Working on innovation and proof-of-concept (POC) development, including an AI-powered framework for automated generation of test cases, enhancing testing efficiency and coverage.

Cloud Infrastructure & DevOps Automation

• Designed and optimized CI/CD pipelines using Azure DevOps and GitHub Actions, enabling zero-downtime, high-frequency deployments across distributed environments.
• Architected Infrastructure-as-Code (IaC) frameworks across Azure and AWS using Terraform, enforcing security, compliance, and operational consistency through automation.
• Implemented end-to-end observability with Datadog, Prometheus, and Grafana, providing real-time visibility into system performance and cloud operations.

Enterprise Automation & Integration

• Developed Python-based automation tools for on-demand infrastructure provisioning, ServiceNow workflows, and VMware–Commvault orchestration, enhancing operational agility.
• Re-engineered legacy scripts into modular, test-driven Python frameworks integrated with enterprise DevOps pipelines, improving reliability and maintainability.

Data Engineering & Transformation Projects

• Designed and deployed end-to-end data transformation pipelines to convert SAS-based enterprise datasets into Oracle Fusion templates using Pandas and Airflow.
• Automated ETL workflows with intelligent scheduling, monitoring, and logging, resulting in a 70% reduction in manual data processing time and faster reporting cycles.