Gilberto Hernandez
Gilberto has spent over a decade shaping technical developer education worldwide. To date, he's made complex concepts accessible to over 100,000 students and engineers through both online learning platforms and in-person experiences.
At Codecademy, he authored and launched several of their foundational courses. Since then, he's worn multiple hats as both product manager and technical content creator at industry leading companies, including MongoDB, Domino Data Lab, Plaid, and Snowflake.
Gilberto is passionate about crafting exceptional developer experiences and educational resources. He frequently writes about data engineering, AI, and application development.
Connect with him on LinkedIn: https://www.linkedin.com/in/gilberto-hernandez/
Session
In this hands-on tutorial, you'll go from a blank notebook to a fully orchestrated data pipeline built entirely in Python, all in under 90 minutes. You'll learn how to design and deploy end-to-end data pipelines using familiar notebook environments, using Python for your data loading, data transformations, and insights delivery.
We'll dive into the Ingestion-Tranformation-Delivery (ITD) framework for building data pipelines: ingest raw data from cloud object storage, transform the data using Python DataFrames, and deliver insights via a Streamlit application.
Basic familiarity with Python (and/or SQL) is helpful, but not required. By the end of the session, you'll understand practical data engineering patterns and leave with reusable code templates to help you build, orchestrate, and deploy data pipelines from notebook environments.