How I Passed Databricks Data Engineer Professional Exam

How I Passed Databricks Data Engineer Professional Exam


8 min read


You've aced the Databricks Data Engineer Associate Exam – congrats! Or maybe, you’re just curious as you heard someone becoming a Certified Data Engineering Professional. Guess it’s time to set your data engineering career in motion.

But where do we start? Let's dive in and explore why this certification is essential in the first place.

The Importance of Databricks Certification in Data Engineering

The Databricks Certified Data Engineer Professional Certification Exam evaluates your proficiency in utilizing Databricks for advanced data engineering tasks. Among the top data certifications, let’s understand why it is important to earn this professional certificate for your data engineering career:

  • Key Cloud Platform for Data Tasks: Databricks stands out as a crucial player in cloud platforms, particularly in data engineering, data science, machine learning, and AI.

  • Leadership in Data Storage Technology: Its robust storage capabilities enable organizations to securely store and manage large volumes of data, facilitating effective data processing and analysis.

  • Innovative Solution with Delta Lake: Databricks introduces an innovative solution powered by Delta Lake, a technology that combines the features of a data warehouse and a data lake.

Figure 1: A chart showing elements of Delta Lake

  • Foundation in Spark: Databricks, built by the creators of Apache Spark, relies on Spark as its core. Integrated with MLflow, Delta Lake, and PyTorch, Databricks offers a comprehensive solution for efficient data processing and advanced machine-learning tasks. This makes Databricks a preferred choice for organizations dealing with large-scale data processing tasks.

Preference Among Large Companies: Its user-friendly interface, advanced features, and seamless integration with existing workflows makes it a preferred choice for organizations seeking to harness the power of their data effectively.

Henceforth, it not only validates proficiency in handling complex data challenges but also positions individuals as sought-after candidates in the competitive job market. That being said, passing the Databricks Associate Exam for Data Engineering is not a prerequisite for this Professional Exam, but it is a wise step to clear the base before setting yourself up for an advanced level.

Quick Insights into the Exam Structure

The Certified Data Engineering Professional exam is more challenging than the associate certification as it delves deeper into topics rather than covering a broad range. It demands you to have at least more than a year of hands-on experience in performing data engineering tasks (as per the exam guide).

Here is a briefly detailed topic-wise structure of what this exam covers:

  • Databricks Tooling (20%): Master Databricks platform and tools like web app, DBSQL queries, and APIs (DBUtils, MLflow). Learn Apache Spark, Delta Lake, and Databricks CLI and REST API for data processing.

  • Data Processing (30%): Build batch and incremental ETL pipelines, optimize workloads, deduplicate data, and use Change Data Capture (CDC) techniques efficiently.

  • Data Modeling (20%): Understand Lakehouse architecture, optimize data layouts, and grasp key data modeling concepts like keys, constraints, and slowly changing dimensions.

  • Security & Governance (10%): Secure data pipelines, manage permissions, handle PII securely, and ensure compliance with regulations like GDPR & CCPA.

  • Monitoring & Logging (10%): Set up alerting mechanisms, use SparkListener for monitoring job execution, record metrics, and navigate Spark UI for debugging.

  • Testing & Deployment (10%): Manage dependencies, implement unit and integration testing, schedule jobs, version code and notebooks, and orchestrate job workflows for production.

A Winning Databricks Certification Strategy: 3 Steps to Success

The heading suggests that I'll discuss a winning strategy for acing this exam. What I haven't mentioned yet is that it's also the simplest path to achieving a professional level in Data Engineering. So, let's kick things off with the first step – Preparation.

Figure 4: Databricks’ guide to exam preparation

Step-1: Preparation

Understanding the exam's ins and outs is key, as Databricks rightly suggests. Remember Epictetus' wise words: "It is impossible for a man to learn what he thinks he already knows." So, take the time to train according to your learning style. It's the best way to grasp the exam's structure, objectives, and expectations. It might not sound thrilling, but it's crucial for success.

Figure 3: Databricks Training Portal

And just like you wouldn't dive into a data project without clarifying its goals, tackling an exam without understanding its parameters is unwise. But which platform to rely upon? Mainly there are two resources that are best suited for your preparation. To access customer learning or partner learning portals of Databricks, you must be in a partner or customer organization. Apart from this training course, it will be great for your learning if you’d take on this Udemy preparation course by Derar Alhussein for Databricks Certified Data Engineer Professional.

Figure 4: Preparation Course on Udemy

Here's a quick overview of what's covered in this prep course that made passing the exam a breeze:

  1. Modelling Data Management Solutions: This section focuses on understanding various data modeling techniques and strategies for effective data management. You'll learn about different data models, such as relational, document-oriented, and graph databases, and how to apply them in real-world scenarios.

  2. Data Processing: Here, you'll delve into the intricacies of data processing, including data ingestion, transformation, and integration. You'll explore tools and frameworks like Apache Spark for processing large-scale data efficiently and learn best practices for handling complex data processing tasks.

  3. Improving Performance: This module covers techniques for optimizing data processing performance. You'll learn how to fine-tune your data pipelines, optimize queries, and leverage caching mechanisms to improve overall performance and efficiency.

  4. Databricks Tooling: In this section, you'll gain a comprehensive understanding of the Databricks platform and its various developer tools. You'll learn how to use tools like Apache Spark, Delta Lake, MLflow, and the Databricks CLI and REST API to build and manage data pipelines effectively.

  5. Security & Governance: This module focuses on security best practices and governance policies for managing data securely within the Databricks environment. You'll learn about data encryption, access controls, auditing, and compliance standards to ensure data integrity and confidentiality.

  6. Testing & Deployment: Here, you'll explore strategies for testing and deploying data engineering solutions. You'll learn how to write unit tests, perform integration testing, and automate deployment processes to streamline the development lifecycle and ensure reliability.

  7. Monitoring & Logging: The final module covers monitoring and logging techniques for tracking and troubleshooting data engineering workflows. You'll learn how to set up monitoring tools, analyze logs, and identify performance bottlenecks to maintain system health and reliability.

Overall, the Databricks Certified Data Engineer Professional Preparation course provides comprehensive coverage of essential topics in data engineering, equipping you with the knowledge and skills needed to excel in the certification exam and in real-world data engineering scenarios.

Step-2: Documentation Portal/Notes

Having built a documentation portal or notes where you can always go back to and revise the concepts before the exam is the most basic and yet, essential advice I can give you. Down below is the example of how I make my easily accessible personal notes using Notion and I would recommend the same for you.

Figure 5: An image of personal notes on Notion

Here's a step-by-step guide to creating easily accessible personal notes using Notion (or any note-taking tool of your choice):

  • Capture Key Information: While going through your Udemy course, take screenshots of important slides or concepts that you want to remember.

  • Note Down Concepts: After capturing screenshots, jot down the key concepts, explanations, or additional notes that accompany them. Keep your notes concise but informative.

  • Organize with Toggles: In your note-taking tool, create a separate section for each topic or section of the course. Within each section, use toggles to hide or show detailed notes. This allows you to keep your notes organized and easily navigable.

  • Include Screenshots: Embed the screenshots you captured earlier into your notes. This visual aid can help reinforce your understanding of the concepts.

Figure 6: An image showing visual interpretation of a data engineering concept

  • Review and Revise: Regularly review your notes to reinforce your understanding of the material. Use them as a quick reference guide when preparing for the exam.

  • Adapt to Your Learning Style: Customize your notes to suit your learning preferences. You can add color-coded labels, highlight important points, or incorporate other elements that enhance your learning experience.

By following this method, you'll have a comprehensive documentation portal that consolidates all the essential information from your Udemy course. It's a convenient way to review and revise the concepts, ultimately improving your chances of success on the exam.

Step-3: Mock Exam

As you wrap up your preparation for the certification exam, consider incorporating mock exams into your study routine. With countless resources available online, including those provided by Databricks, exploring mock tests and courses can greatly enhance your chances of success. As already mentioned earlier, Alhussein's comprehensive course offers practice questions closely aligned with the exam format. Enrolling in this course can provide valuable insights into potential exam questions, helping you solidify your understanding of key concepts.

Additionally, for personalized notes and practice exam questions, you can visit my notion page. Incorporating mock exams into your preparation strategy is a vital step towards ensuring readiness and confidence on exam day.


At last, I can guarantee that mastering the Databricks Data Engineer Associate Exam is a challenging yet rewarding journey towards becoming a Certified Data Engineering Professional. By staying curious and keeping up with evolving trends in data engineering, professionals can excel in their roles and establish themselves as leaders in the field. Seize the opportunity, expand your skills, and embark on the path to certification – your future self will thank you. Check out my YouTube video for more insights.

So, seize the opportunity, expand your skill set, and embark on the path to becoming a Certified Data Engineering Professional – your future self will thank you for it. To hear more on this from me, you can check my YouTube video below.