Building Your First ETL Pipeline Using Azure Databricks
Data pipelines are now table stakes—not nice-to-haves. This course gets you building production-ready ETL workflows on Azure Databricks in under 3 hours, with real sandbox labs you can execute immediately. You’ll move from theory to deployable code faster than most bootcamps.
AIU.ac Verdict: Ideal for cloud engineers, data engineers, and DevOps professionals who need to ship ETL solutions on Azure without weeks of self-study. The 2h 40m duration is a strength for busy practitioners, though you’ll want foundational Azure knowledge beforehand to maximise the hands-on labs.
What This Course Covers
You’ll start with ETL fundamentals and why Databricks solves the orchestration problem, then move directly into building your first pipeline using Databricks notebooks and Delta Lake. The course covers data ingestion patterns, transformation logic, and job scheduling—all within the Azure ecosystem. Expect to work with real datasets and learn how to handle common pipeline failures.
Mohit walks you through practical scenarios: connecting to Azure Data Lake Storage, writing scalable Spark transformations, and monitoring pipeline health. You’ll use Databricks’ collaborative notebooks and understand how to structure code for production environments. The sandbox labs let you execute everything in real time, so you leave with working code you can adapt to your own projects.
Who Is This Course For?
Ideal for:
- Cloud engineers transitioning to data: You know Azure fundamentals but need to understand data pipeline architecture. This course bridges that gap without overwhelming you with data science theory.
- Data engineers building on Azure: You’re ready to move beyond SQL scripts into orchestrated ETL. Databricks is the industry standard; this course gets you productive in hours, not weeks.
- DevOps professionals expanding into data ops: You understand CI/CD and infrastructure. ETL pipelines follow similar patterns; this course translates your existing mindset into Databricks workflows.
May not suit:
- Complete Azure beginners: You’ll struggle without foundational Azure knowledge (storage accounts, authentication, resource groups). Start with Azure fundamentals first.
- Data scientists seeking ML pipelines: This course focuses on data movement and transformation, not model training or inference. It’s ETL, not ML Ops.
Frequently Asked Questions
How long does Building Your First ETL Pipeline Using Azure Databricks take?
2 hours 40 minutes of video content. Most learners complete it in one or two focused sessions. Add 1–2 hours if you’re repeating labs or experimenting beyond the course scope.
Do I need Azure experience before starting?
Yes. You should be comfortable with Azure basics: storage accounts, resource groups, and authentication. If you’re new to Azure, complete an Azure fundamentals course first.
Will I have hands-on labs?
Absolutely. Pluralsight provides sandbox environments where you execute real Databricks notebooks and pipelines. You’re not just watching—you’re building.
Is this course suitable for production-ready knowledge?
It’s a strong foundation. You’ll understand pipeline architecture, Delta Lake, and Databricks workflows. For enterprise deployments, you’ll want to supplement with your organisation’s specific governance and security requirements.
Course by Mohit Batra on Pluralsight. Duration: 2h 40m. Last verified by AIU.ac: March 2026.
