Job-Ready GCP & Airflow Data Engineering Projects with Diksha Chourasiya

Two real-world data engineering projects you can build, add to your resume and confidently discuss in interviews.

Recruiters shortlist candidates who can show hands-on pipeline experience, not just a list of tools. This bundle gives you two complete, guided projects covering skills hiring teams ask about most: Spark on GCP Dataproc and Apache Airflow orchestration.

Project 1: GCP Data Engineering Pipeline (Dataproc)

• Set up a Dataproc cluster and run PySpark jobs
• Process data at scale with Apache Spark
• Read from and write to Google Cloud Storage
• Step-by-step walkthrough with screenshots
• Interview questions mapped to this use case

Project 2: Airflow Pipeline with Docker

• Deploy Airflow locally using Docker
• Build, schedule and monitor DAGs end to end
• Handle orchestration, dependencies and failures
• Quick to set up, with a cloud-ready design

What Makes This Different

• Portfolio-ready: two projects to showcase on your resume
• Interview-focused: questions tied directly to the pipelines you build
• Hands-on: annotated screenshots, clear explanations and working code
• Beginner-friendly, yet practical: start with Airflow on Docker, then scale up to GCP

Who This Is For

• Aspiring and early-career Data Engineers
• Professionals moving into cloud data engineering
• Candidates who need real projects to talk about in interviews

Even before you finish both builds, you will walk away with solid architecture knowledge and strong interview talking points.

About the Creator

Created by Diksha Chourasiya, Senior Data Engineer with 6+ years of experience designing data pipelines on Google Cloud, and a GCP educator to a 20K+ LinkedIn community.