video1.0<iframe src="https://www.loom.com/embed/babdb42fa6ef493b8bfefc547f9689f0" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/babdb42fa6ef493b8bfefc547f9689f0-23b6e9d990ff3e2c.jpg1104.272In this video, I walk you through a hands-on data engineering project where I designed and implemented an end-to-end ETL pipeline for a fictional e-commerce company called Novacard. The project utilizes Databricks and Delta Lake, following the medallion architecture to transform raw transactional data into meaningful business insights. I detail the steps from ingesting the data to cleaning and enriching it, ultimately aggregating it to compute total sales and average order value. I also highlight the use of Delta Lake features for data governance and optimization. I encourage you to consider how similar approaches could enhance our own data workflows.