[100% Off] Databricks Certified Data Engineer Associate- Practice Exam

Master the skills and knowledge to excel in the Databricks Certified Data Engineer Associate exam

Added on October 7, 2025 IT & Software 2 min read

What you’ll learn

Assesses an individual’s ability to use the Databricks Data Intelligence Platform to complete introductory data engineering tasks
Assesses the ability to perform ETL tasks using Apache Spark SQL or PySpark
covering extraction
complex data handling and User defined functions.
The exam assesses the tester’s ability to deploy and orchestrate workloads with Databricks workflows configuring and scheduling jobs effectively.
Who pass this certification exam can be expected to complete basic data engineering tasks using Databricks and its associated tools.

Requirements

None

Description

Databricks Certified Data Engineer Associate Preparation

This course is designed to prepare learners for the Databricks Certified Data Engineer Associate certification exam, which validates the foundational skills required to work with the Databricks Data Intelligence Platform. Participants will gain hands-on experience in building and managing data pipelines, performing transformations with Apache Spark, and implementing governance and quality controls using Unity Catalog.

Through a combination of lectures, demonstrations, and practical exercises, learners will explore the Databricks workspace, understand its architecture, and develop the ability to use Databricks tools effectively in real-world data engineering scenarios.

The course covers:

Databricks Intelligence Platform: Core features, compute options, and performance optimization.
Development and Ingestion: Using Databricks Connect, Auto Loader, and notebooks for scalable data ingestion workflows.
Data Processing & Transformations: Applying the Medallion Architecture, Spark SQL/PySpark operations, and building optimized pipelines.
Productionizing Data Pipelines: Deploying, monitoring, and troubleshooting workflows with Databricks Asset Bundles, Jobs, and the Spark UI.
Data Governance & Quality: Managing permissions, lineage, and secure data sharing with Unity Catalog and Delta Sharing.

By the end of this course, participants will be able to:

Confidently perform ETL and data engineering tasks in Databricks.
Design and implement efficient data pipelines following best practices.
Apply governance and data-sharing strategies across teams and systems.
Be fully prepared to sit for the Databricks Certified Data Engineer Associate exam.

Prerequisites: No formal prerequisites. However, basic SQL knowledge and six months of hands-on Databricks experience are recommended.

Target Audience: Aspiring data engineers, analysts transitioning to engineering roles, and professionals seeking Databricks certification to demonstrate foundational skills in data engineering.