Sree Ranjani M

Experienced full-stack application developer specializing in building microservices and web applications. Proficient in Node.js, SQL, and React, with a strong desire to expand knowledge in new tech stacks. Committed to ongoing learning and staying current with emerging technologies to drive innovation and deliver impactful solutions.

Government Healthcare Project

Tech Stack: Node.js, Typescript, NestJS, ExcelJS, Puppeteer, MySQL, Postgres, Azure VMs, Kubernetes, Blob Storage, HTML

• Built dynamic Excel and PDF reports for healthcare professionals using ExcelJS and Puppeteer, enabling data-driven decision-making and operational insights.
• Engineered cross-database integrations using federation between MySQL and Postgres, optimizing complex queries for performance across distributed servers.
• Enhanced system reliability and performance by introducing functional test suites at the code level and optimizing large-scale SQL query execution.
• Utilized Azure cloud infrastructure, including VMs, Kubernetes, and Blob Storage, for log tracing, container orchestration, and secure file management.

Procurement | Consulting Firm

Tech Stack: Node.js, Hapi.js, React, Redux, Postgres, Azure AI, Argo Workflows, Trino, Splunk

• Led end-to-end development of scalable procurement features using Node.js, Hapi.js, and React, including role-based admin views, secure APIs, and multi-category categorization modules.
• Implemented robust automation with Argo Workflows and Rclone to streamline data pipelines and enable Azure AI/ML model training, enhancing system efficiency and scalability.
• Optimized data infrastructure, executing bulk migrations and queries with Trino and Postgres; integrated PowerBI for client-specific dashboards and cross-tenant data insights.
• Strengthened system quality and security through rigorous unit/integration testing (Jest), load testing (Locust), JOI validations, and pentesting practices.

Client Data Master | Consulting Firm
Tech Stack: JavaScript, APIGEE, Snaplogic, Splunk

• Unified disparate client data sources into a clean, structured data model to support future predictive analytics on client engagement and retention.
• Developed and maintained scalable APIs using APIGEE, enabling seamless integration across system components and third-party tools.
• Automated communication workflows via Snaplogic, building efficient data pipelines and streamlining data exchange within the ecosystem.
• Optimized search algorithms to maintain high performance and responsiveness while processing over 150,000 client records.