Developed and implemented end-to-end big data pipelines for advertising analytics using cloud-based solutions, including serverless data preprocessing, automated metadata management, and scalable ETL workflows with Snowflake and Informatica. Leveraged Snowpark, Python, and PySpark for advanced data transformations, optimizing real-time data ingestion and enhancing data quality. Orchestrated workflows with Airflow and created actionable dashboards to support business-critical insights and comprehensive reporting.

As a Teaching Assistant for the courses Computer Science 1 Laboratory (CPSC 1011), Introduction to Programming in C (CPSC 1111), and Computer Organization Laboratory (CPSC 2310), I actively support students in programming labs and computer organization, fostering an engaging learning environment and assisting the course instructor with the grading responsibilities

As an integral member of the Probe Technical Symposium organizing committee and Publicity Team, I played a pivotal role in coordinating and executing various technical events. My efforts significantly contributed to enhancing overall engagement and attendance by conducting outreach initiatives, including university visits, to extend invitations and generate interest among prospective participants.

Worked on a Python data pipeline for large-scale student data using pandas and numpy, improving processing efficiency and data accuracy. Performed complex SQL queries and Excel analysis to derive valuable insights, visualized through Tableau dashboards featuring detailed data maps and correlation plots for trend analysis. Python and SQL analysis identified key performance areas, enabling targeted improvements in critical metrics. Presented data-driven recommendations to executives, facilitating strategic decision-making and optimizing educational outcomes.