Muhammad Ghufran

Designed and maintained ETL pipelines using Snowflake, dbt, AWS Glue, and S3. Automated data ingestion and transformation for reliable workflows. Built and optimized Snowflake data models for faster queries. Integrated S3 for secure storage and analytics, ensuring high data quality and performance.

Designed and maintained end-to-end Snowflake data pipelines and medallion architecture, improving data reliability and reducing query latency through Snowpark optimizations and clustering strategies.

Resolved production bugs and improved application stability while creating reusable React components and responsive recruitment portal pages. Led a Webpack migration (v1→v3) and implemented a generic AJAX module to standardize client-server calls.

Built RAG systems and LLM-powered chatbots and developed AI pipelines and real-time data processing with Kafka, Spark, and Snowflake to deliver production ML solutions.

Grade: 3.5

Activities and societies: outdoor and indoor activities

Earned a Bachelor of Science in Computer Science at the National University of Sciences and Technology, Islamabad, from 2012 to 2016.

Completed a Bachelor's degree in Computer Science with coursework and projects focused on software engineering and data systems from Feb 2015 to Aug 2019.