Data Engineering ⁴⁰

2026

Streaming Foundations I: Redpanda and Python Producers 03-13

Running Spark in the Cloud: GCS, Standalone Clusters, and Dataproc 03-07

Spark Internals: Clusters, Shuffles, Joins, and RDDs 03-06

Spark SQL: Running SQL Queries on DataFrames 03-05

Getting Started With PySpark: Sessions, DataFrames, and Transformations 03-04

Batch Processing Fundamentals & Introduction to Apache Spark 03-03

From API to Warehouse in Minutes: Building a Dlt Pipeline With AI 02-27

Understanding Dlt: The Modern Python Library for Data Ingestion 02-27

Advanced Bruin Workflows: AI Agents & Cloud Deployment 02-23

Building an End-to-End Data Pipeline With Bruin 02-19

Introduction to Modern Data Platforms & Bruin Basics 02-15

Dbt Deployment: Commands and CI/CD 02-14

Dbt Testing, Documentation, and Packages 02-13

Dbt Models: Subqueries, CTEs, and Macros 02-12

Dbt Project Setup: Structure, Sources, and Staging 02-11

Dbt Architecture: Core, Cloud, and the Future With Fusion 02-10

Analytics Engineering Basics & Introduction to Dbt 02-09

Snowflake Architecture: Solving Pain Points With 'Separation of Storage and Compute' 02-05

Optimizing BigQuery: Partitioning, Clustering, and ML 02-05

BigQuery Internals: The Serverless Data Warehouse 02-04

1
2