Azure Databricks & Spark for Data Engineers:Hands-on Project (Udemy.com)
[Fully Refreshed 2026] Real World Project on Formula1 using Databricks, Spark, Delta Lake, Unity Catalog, Lakeflow Jobs
Created by: Ramesh Retnasamy
Last updated May 2026
What you will learn
- You will learn how to build a real world data project using Azure Databricks and Spark Core. This course has been taught using real world data.
- You will acquire professional level data engineering skills in Azure Databricks, Delta Lake, Spark Core, Azure Data Lake Gen2 and Azure Data Factory (ADF)
- You will learn how to create notebooks, dashboards, clusters, cluster pools and jobs in Azure Databricks
- You will learn how to ingest and transform data using PySpark in Azure Databricks
- You will learn how to transform and analyse data using Spark SQL in Azure Databricks
- You will learn about Data Lake architecture and Lakehouse Architecture. Also, you will learn how to implement a Lakehouse architecture using Delta Lake.
- You will learn how to build and orchestrate data pipelines using Lakeflow Jobs in Databricks.
- You will learn how to implement incremental data processing using Delta Lake.
Course Description
Course Fully Refreshed for 2026
This course has been completely rebuilt for 2026 using the latest Azure Databricks features and best practices.
Instead of relying on legacy approaches such as Hive Metastore and external orchestration tools, this course focuses on modern Databricks capabilities like Unity Catalog, Lakeflow Jobs, Databricks SQL Dashboards, and Genie.
Welcome!
In this course, you will build a complete end-to-end data engineering project using Azure Databricks and Apache Spark based on Formula 1 Motor Racing data.
You won’t just learn individual concepts. You will design and implement a cloud data platform from scratch, following the same approach used in real-world data engineering and data platform projects.
What You Will Build
Throughout the course, you will:
Design a modern Data Lakehouse architecture using Azure Databricks
Implement the Medallion Architecture (Bronze, Silver, Gold) for scalable data pipelines
Ingest, transform, and model data using Apache Spark (PySpark and Spark SQL)
Store and manage data using Delta Lake in Databricks
Organise and govern data using Unity Catalog in Azure Databricks
Build and orchestrate pipelines using Lakeflow Jobs in Databricks
Create analytical views and dashboards using Databricks SQL and Dashboards
Enhance the pipeline with incremental data processing using Delta Lake
By the end of the course, you will have built a production-ready data engineering pipeline on Azure Databricks.
Technologies You Will Use
As part of building the project, you will learn:
Azure Databricks
Apache Spark using PySpark and Spark SQL
Delta Lake and modern Lakehouse architecture
Unity Catalog for data governance and organisation in Databricks
Databricks SQL and Dashboards for analytics and reporting
How You Will Learn
This is a hands-on, project-based Azure Databricks course.
You will build the solution step by step
Concepts are explained in the context of a real-world project
Each section builds on the previous one
This approach ensures that you not only understand the concepts, but also know how to apply them in real-world data engineering scenarios.
I value your time as much as I do mine. So, I’ve designed this course to be focused, practical, and to the point. The lessons are explained in simple English, without unnecessary jargon, and we start from the basics. By the end of the course, you will be confident building real-world data engineering solutions.
How This Course Supports Certification Preparation
This course can help you build many of the core skills required for the following certifications:
Databricks Certified Data Engineer Associate
Databricks Certified Associate Developer for Apache Spark
Microsoft Exam DP-750: Implementing Data Engineering Solutions Using Azure Databricks
Databricks Certified Data Engineer Professional
The hands-on project will strengthen your practical understanding of key Databricks and Spark concepts tested in these exams.
However, this course is not designed as a certification preparation course and does not cover all exam topics.
What’s Included (and What’s Not)
This course focuses on core Spark and Databricks concepts
It does not cover Spark Streaming, Spark ML, and Lakeflow Declarative Pipelines
Spark is taught using PySpark and Spark SQL (not Scala or Java)
Final Outcome
By the end of this course, you will have built a complete, production-ready data engineering solution using Azure Databricks and Spark, and gained the confidence to apply these skills in real-world projects.
Instructor Details
- 4.7 Rating
28,183 Reviews
Ramesh Retnasamy
Hello! I am a full-time Senior Data Engineer and Architect with over 25 years of experience delivering large scale data projects across industries including technology, gaming, finance, retail, and government.
I have worked extensively on cloud platforms such as Azure and AWS, as well as on-premises systems. I hold multiple certifications, including Data Engineering credentials from Microsoft Azure and Databricks.
Teaching is a passion of mine, and I take great pride in the success of my students. My approach is different from traditional IT training. I focus on real world projects that not only explain the concepts but also help them stick through hands-on application. I provide guidance on best practices and help you build solutions that are ready for real production environments.
I value your time as much as mine, so I keep my courses focused, practical, and free of jargon. All lessons are taught in simple English. By the end of my courses, you will have the skills and confidence to begin working on real projects, along with a strong foundation to continue learning and growing in your career.
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Reviews
By Abhinandan Samal on 8/22/2026
I was new to Azure Databricks & this course gave me really good hands-on understanding. I am now confident to apply the learnings from this course in real world projects. Thank you for creating such a nice course. I will recommend this course to everyone who wants to learn Azure Databricks.
By Wai Kwok Chan on 7/22/2026
The instructor can detailly explaining each step and he have prepared the course material in a very good way. Beginner can catch up databricks from zero to an intermediate level of understanding how to use databricks. Although the last few lessons in explaining the batch update process is a little bit difficult, but the overall course are worth to take if you want to learn databricks from zero with the prerequisite of basic to intermediate level knowledge of Python and SQL. Thank you for preparing this course, thumbs up for it and hope you can continue to do that.
By Kassu Wodajo on 7/15/2026
This is an excellent course. The instructor is extremely knowledgeable, and I really appreciate that the course focuses much more on practical, hands-on examples than just theory. The content is well structured and builds concepts in a logical way, making it easy to follow. To get the most out of this course, I highly recommend following along with the instructor and completing the hands-on exercises rather than just watching the videos. The practical examples reinforce the concepts and make them much easier to understand. I'm an integration developer, and I'm currently working on redesigning some of our applications to leverage Databricks. This course covers the majority of the topics I need for my work and has given me a solid foundation to move forward with confidence. The only addition I would have liked is a section on how Databricks can call or integrate with external services or APIs. However, that's a minor suggestion and certainly not a deal breaker. Overall, I highly recommend this course to anyone looking to learn Databricks through real-world, practical examples.
By Kiran Candy on 6/18/2026
This course follows a hands-on, learn-by-doing approach, which makes it much more effective than theory-only learning. As a beginner in Data Engineering, I am able to understand concepts better by applying them in practice. I would highly recommend this course to other beginners
By Aman Pandey on 6/4/2026
Great Course, gives you an understanding of Databricks Architectural setup to creating notebooks and finally using lakeflow jobs to orchestrate the data pipelines. Covers only py-spark basics so if you want to deep dive in py-spark coding, this could only be a starter course for you.
By Pranay Uttamchandani on 5/20/2026
Got done implementing this project! Medallion-style architecture was such useful thing to learn along with Databricks. What I liked about this project was diversity. For example, he went through different scenarios for file ingestions: CSV, json, nested json and explained 3 different modes with which we can ingest it. Practical stuff. In addition, this project followed best practices like writing modular codes and how can they later be executed using Lake Flow jobs. A great course that hits the basics! Thanks Ramesh for all the effort. This is something that I needed and was well executed. My 2 cents: I would put theory explanations after the project. So while doing the project, one can reference videos to later sections for a deeper understanding. I felt like quitting in the beginning due to lot of theory/explanations, but once I got my hands on the project, I managed to get things done and enjoyed it. Great stuff!
By Arunesh on 5/14/2026
Updated course content help me allot to complete the project. Somehow i managed ,but struggling to manage with legacy setup
By Pratik Shah on 3/23/2026
This is the best course to learn Databricks. All the topics are covered in great depth. The attention to details is fantastic. Hats-off to the Author for the great work. You will not get any course that covers all these topics. Thanks!!!
By Onir on 2/26/2026
I completed this course back in 2024. Passed my Databricks DE professional cert as well. I am revisiting this course as I am recertifying for the same. This is one of the best and well structured course I must say. I hope Mr. Ramesh creates a wonderful course like this covering ML with Databricks. Thank you. Good luck to fellow learners :)
By Madhuvanthi Sridhar on 1/29/2026
It started off so good! Until the joins lecture I felt like I was following along and understanding everything so well. After that, it just felt a bit rushed and too quick for me to process. I was having to go back and watch or slow down each video which was taking me forever. Hence the rating.
Quality Score
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Overall Score : 94 / 100







