Pipeline From DA To DE (Course)

Stop cranking out dashboards and start building the pipelines that feed them.

This 8-module track is your blueprint for transitioning from Analyst to Engineer using the 2026 data stack.

Module 1: The Architect's Mindset

Stop thinking like a report-builder and start thinking like a system designer. We’ll bridge the gap between business requests and production reality, teaching you the mental frameworks needed to own the data lifecycle.
Module 2: Advanced SQL-From Querying To Building

Master the "Data Engineer's SQL." Move beyond simple SELECT statements into DDL, DML, and building resilient, cost-effective schemas that don't break under high-volume pressure.
Module 3: The Automation Engine

Put down the Jupyter Notebook. Learn to use Python as a production-grade automation tool for interacting with APIs, handling complex JSON structures, and building scalable ETL logic.
Module 4: The Cloud Stack

Infrastructure is the engineer’s playground. We’ll dive into the Google Cloud ecosystem to master IAM, Service Accounts, and Virtual Machines—the essential "passport" to professional cloud engineering.
Module 5: Introduction to Orchestration

Move from "manual execution" to "hands-off automation." Learn how to use Airflow and Cloud Composer to schedule, monitor, and manage complex DAGs that run while you sleep.
Module 6: Defensive Engineering & QA

Engineers don’t just fix errors; they prevent them. This module covers testing frameworks, metadata validation, and the art of "backfilling" data without breaking your existing production tables.
Module 7: Cost & Performance Optimization

Accuracy is only half the battle; scale and cost are the other. Learn how to optimize BigQuery performance, estimate storage costs, and keep your cloud bills low while your data volume grows.
Module 8: Showcasing Your Work

Tie it all together by building a production-ready asset. We'll focus on creating an end-to-end pipeline that proves your engineering competence to hiring managers and technical leads.