Yellow Capsule Medical

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

Anonymous published on 2026-02-27 included in Data Engineering

Goal: Build a complete, working data pipeline — from the Open Library API to a local DuckDB database — using dlt, an agentic IDE (Cursor), and the dlt MCP server. You write one prompt; the AI writes the code.

1. What You’ll Build

By the end of this workshop, you’ll have:

Understanding Dlt: The Modern Python Library for Data Ingestion

Anonymous published on 2026-02-27 included in Data Engineering

Goal: Understand what dlt (data load tool) is, why it exists, and how its core Extract → Normalize → Load architecture solves one of the most tedious problems in data engineering: getting data from a source into a warehouse, reliably and repetably.

1. The Ingestion Problem

In the modern data stack, getting data into a warehouse is often the most unglamorous part of the job. You need to:

Advanced Bruin Workflows: AI Agents & Cloud Deployment

Anonymous published on 2026-02-23 included in Data Engineering

Goal: Explore advanced Bruin capabilities by integrating AI agents via the Model Context Protocol (MCP) to automate pipeline creation, and deploying our workflows to Bruin Cloud for fully managed orchestration.

1. Supercharging Development with Bruin MCP

One of the most powerful features of the modern data stack is the integration of Artificial Intelligence. Bruin supports the Model Context Protocol (MCP), allowing AI agents (like Cursor, GitHub Copilot, or Claude) to interact directly with your Bruin project.

Building an End-to-End Data Pipeline With Bruin

Anonymous published on 2026-02-19 included in Data Engineering

Goal: Learn how to transition from theory to practice by building an end-to-end data pipeline locally using Bruin and DuckDB, processing NYC Taxi Data.

1. Getting Started: Installation & Setup

Before building our pipeline, we need to set up Bruin on our local machine.

Introduction to Modern Data Platforms & Bruin Basics

Anonymous published on 2026-02-15 included in Data Engineering

Goal: Understand the need for unified data platforms in the modern data stack and learn the fundamental concepts of Bruin: Projects, Pipelines, Assets, Variables, and Commands.

1. The Modern Data Stack & The Need for Data Platforms

A typical modern data stack involves several distinct components to move data from source to destination and make it useful for the business:

Dbt Deployment: Commands and CI/CD

Anonymous published on 2026-02-14 included in Data Engineering

Goal: master the dbt Command Line Interface (CLI) and implement efficient CI/CD pipelines.

1. The Essential Commands

While there are many commands, you will spend 90% of your time with these four.