Ngoc Suong Mai

Engineered robust data pipelines to collect, process, and store data from multiple platforms, ensuring data accuracy for the financial product tracking system using Python, Pandas, AWS Step Functions, and Snowflake. Led the team to build scalable data hub applications to analyze, visualize, and report data from diverse sources, reducing reporting time by up to 60% and improving data accuracy and integrity. Migrated legacy applications from Microsoft Azure and on-premises to AWS, improving overall system performance by 50%. Designed and released an AI-powered document query platform using LLMs and Retrieval-Augmented Generation to assist business users in quickly reviewing documents and templates.

Engineered robust data pipelines to collect, process, and store data from multiple platforms for the financial product tracking system using Python, Pandas, AWS Step Functions, and Snowflake. Led the team to build scalable applications on top of a data hub to analyze, visualize, and report data from diverse sources, reducing reporting time by up to 60% and improving data accuracy. Migrated legacy Azure/on-premises infrastructure to AWS, improving performance by 50%. Designed and released AI-powered document query platform using LLMs and Retrieval-Augmented Generation (RAG) to help business users review documents and templates.

Contributed to development of trading/stock market information app by deploying Python microservices (Flask, Celery) on Google Cloud using Kubernetes Engine for scalability and reliability. Built internal DevOps dashboard backend using Python REST APIs and Vue.js to monitor deployment status, server health, and release cycles; supported real-time insights for release managers. Developed scalable automation frameworks across web/mobile/networking platforms embedded into Jenkins CI/CD pipelines.