Saad Ahmed

Led the development and training of Text-to-SQL LLMs, validating them on Snowflake Marketplace databases. Partnered with Snowflake to enhance their Copilot feature and co-developed a Retrieval-Augmented Generation (RAG) tool for unstructured data.

Built scalable ETL pipelines using Azure Data Factory, PySpark, and SQL for seamless data integration. Developed Azure Functions integrated with Cosmos DB and Service Bus, and implemented EDI/NON-EDI solutions for cross-entity data exchange.

Built interactive Tableau dashboards to track and visualize key metrics for Controlling and Finance departments. This enabled data-driven decision-making and improved financial insights.

Developed a Customer Experience Platform for automotive clients using MS SQL Server, designing and implementing SSIS packages for data consolidation. Engineered a hybrid data infrastructure with SQL Server and MongoDB to accelerate data retrieval and improve operational efficiency.

Developed a real-time Medical Emergency System for Punjab Medical Services (1122) using MySQL, MongoDB, Node.js, Laravel, and Vue.js. The system featured vehicle tracking, geo-fencing, and trip monitoring capabilities.

Analyzed Apache server logs using the ELK stack to identify and investigate anomalous behaviors. Applied supervised machine learning techniques to categorize business text messages by industry, improving data classification accuracy.

Pursued a Master of Science in Data Engineering and Analytics, focusing on advanced data processing, machine learning, and big data technologies. Gained expertise in designing and implementing scalable data solutions.

Completed a Bachelor of Science in Computer Science with a minor in Mathematics, covering core principles of computing, algorithms, and mathematical foundations. Developed strong analytical and problem-solving skills.