GCP Data Engineer Track
Build 7 ready-made GCP data pipeline projects using BigQuery, Cloud Storage, Cloud Composer, Dataflow, Pub/Sub, BigQuery ML, Cloud SQL, and dbt.
Source code • Setup files • Architecture diagrams • Implementation videos • Support
GCP TRACK
GCP Data Engineer Track
7 ready-made GCP pipeline projects from batch ingestion to BigQuery transformations, analytics marts, machine learning, exports, and streaming.
BigQuery • Cloud Storage • Cloud Composer • Dataflow • Pub/Sub • BigQuery ML • Cloud SQL • dbt
7 GCP pipeline projects included
Move from ingestion to BigQuery analytics, machine learning, exports, and streaming using real GCP services.
P01 • Batch Ingestion
Design a Dataflow Pipeline from MySQL to BigQuery
Build a watermark-driven MySQL to BigQuery batch ingestion pipeline using Dataflow, staging tables, and Cloud Composer.
View Project →
P02 • File Ingestion
Automate Vendor File Ingestion with Python and Airflow
Automate vendor file ingestion into BigQuery with metadata logs, archive handling, and quarantine routing.
View Project →
P03 • BigQuery Transformation
Orchestrate a BigQuery SQL Transformation Pipeline
Orchestrate BigQuery ELT transformations with SQL stored procedures, refined tables, and Composer DAGs.
View Project →
P04 • Analytics Layer
Create Analytics Marts with dbt and BigQuery
Model refined retail data into reusable dimensions, facts, KPIs, and business marts using dbt on BigQuery.
View Project →
P05 • Business Exports
Automate BigQuery Exports to Cloud Storage
Automate BigQuery exports to Cloud Storage as CSV/Parquet files with audit logs and Composer DAGs.
View Project →
P06 • Machine Learning
Predict Order Returns with BigQuery ML
Train, evaluate, and score a return-risk model in BigQuery ML using SQL and retail order and return data.
View Project →
What you get
Everything needed to build, run, validate, and understand the GCP projects faster.
Source code
Ready-to-use project files and scripts.
Setup files
Guided setup for required GCP services.
Architecture diagrams
Visual flow of how each pipeline works.
Implementation videos
Step-by-step walkthroughs for building the projects.
Validation steps
Checks to confirm your pipeline output.
Support
Ask questions during setup, execution, validation, or architecture understanding.
Questions before you join?
Do I build this in my own GCP account?
Yes. The projects are built inside your own GCP account.
Does this include code and setup files?
Yes. Each project includes source code, setup files, architecture diagrams, implementation videos, validation steps, and Ask support.
What if I get stuck?
You can ask through course discussion or the Data0to1 Ask page.
Should I choose GCP Track or Ultimate Project Library?
Choose GCP Track if you only want GCP projects. Choose Ultimate Project Library if you want AWS, Azure, and GCP projects together.
Ready to build GCP pipeline projects?
Get access to 7 GCP projects with code, setup files, architecture diagrams, implementation videos and support.