00: 00 Data Pipeline Overview
09: 20 Pipeline real Demo
10: 42 Using Docker for Airflow

In this episode, we dive into the orchestration layer of the trading system and explore how Apache Airflow coordinates the entire pipeline from data ingestion to trade execution.

You will learn how a real-world trading bot is structured behind the scenes — not as a simple script, but as a complete data platform. We walk through the full workflow, including data ingestion, processing with dbt, signal generation, and how those signals are finally executed as trades.

We also break down key concepts like:
– The difference between orders and trades
– How positions are reconstructed from raw data
– How trading signals are generated from indicators
– How strategies like Smart DCA and Price Ladder work
– How the system executes trades automatically
– Why orchestration is critical for reliability and scalability

Everything is orchestrated using Airflow and deployed with Docker, making the system reproducible, observable, and cost-efficient.

This is not just about trading — this is about building a real data system that makes automated decisions.

📌 Tech Stack
– Python
– PostgreSQL
– dbt
– Apache Airflow
– Docker

📌 Series: How To Build a Trading Robot
– Episode 3 — Orchestration with Airflow