Course Information
Course Overview
[NEW 2026 SYLLABUS] Databricks Data Engineer | Databricks Certified Data Engineer Associate Certification Exam Prep
Are you ready to become a DATABRICKS DATA ENGINEER [WITH UPDATED 2026 SYLLABUS]?
Whether you're a beginner or a working professional who wants to level up, this course will guide you step by step with a hands-on, practical, and engaging approach.
GAIN STRONG HANDS-ON WITH:
Lakehouse Architecture, Lakehouse Federation, and Lakeflow Connect – Understand how Databricks handles structured and unstructured data, and how Lakehouse Federation lets you query external sources seamlessly.
DATABRICKS ASSET BUNDLES - Learn how to create the CI/CD ready bundles for your development.
Unity Catalog, Metastore, Volumes, and UDFs – Learn how to manage data, permissions, and catalogs efficiently using Databricks’ built-in governance features.
PySpark for Big Data – Master PySpark with real use cases, transformations, actions, joins, and more — all from a Data Engineer’s point of view.
Structured Streaming + Autoloader – Build real-time pipelines using Spark Streaming and learn how Autoloader handles files in cloud storage.
Delta Lake Architecture – Dive deep into Delta’s features like ACID transactions, time travel, schema evolution, and performance tuning.
Databricks SQL Warehouses – Learn how to write parameterized queries, schedule dashboards, and set alerts using SQL Warehousing.
LakeFlow Declarative Pipelines – Work with Streaming Tables, Materialized Views, and build low-code data pipelines.
Delta Live Tables (DLT) – Build robust pipelines with SCD implementation, data quality checks, expectations, and monitoring.
Databricks Git Folders [Repos] - Work with Remote Repo and Local Repo using your Databricks Portal.
Orchestrate ETL with LakeFlow Jobs – Schedule, monitor, and manage your pipelines using LakeFlow Jobs end-to-end.
Security and Sharing – Apply row-level security, data masking, and explore Delta Sharing for secure and scalable collaboration.
What Makes This Course Different?
Super Engaging Lectures – No boring theory here! I explain every concept in a clear and beginner-friendly way using real-life examples and visuals.
Deep Dive into Every Topic – I don’t just scratch the surface. You'll understand the “why” and “how” behind every feature .
Strong Hands-On Focus – Learn by doing! From pipelines to notebooks to warehouse, you’ll build real solutions step-by-step, just like a Databricks Data Engineer does.
DISCLAIMER : This course is independently created and not affiliated with or endorsed by Databricks Inc. All content, including explanations and practice materials, is original and intended solely for educational purposes. It does not include any actual certification exam questions and is based on publicly available documentation, real-world scenarios, and personal experience. Product names, logos, and trademarks used are the property of their respective owners and are included only for identification and learning. Always refer to official Databricks documentation for the latest and most accurate information.
Course Content
- 10 section(s)
- 137 lecture(s)
- Section 1 Course Introduction & Resources
- Section 2 Lakehouse Core Fundamentals
- Section 3 Get Started With Databricks
- Section 4 Unity Catalog - The Complete Guide
- Section 5 Big Data With Apache Spark
- Section 6 [NEW 2026] Databricks Lakehouse Federation & Files
- Section 7 [NEW 2026] Databricks Lakeflow Connect
- Section 8 AUTOLOADER - Spark Structured Streaming
- Section 9 [NEW 2026] Databricks SQL Warehouse
- Section 10 [NEW 2026] Databricks Lakeflow Jobs
What You’ll Learn
- [UPDATED JULY 2025 SYLLABUS] - All the important topics you need to PASS the Certification
- Databricks Asset Bundles and Databricks Repos for CI/CD workflows
- Understand key concepts like Lakehouse Federation, Lakeflow Connect, and the Medallion Architecture
- Strong hands-on with Unity Catalog, Volumes, Metastore, Catalog UDFs, and utils
- PySpark Big Data Crash Course - from basics to real-world use cases
- Master Spark Structured Streaming using Auto Loader for INCREMENTAL real-time data ingestion
- Learn the complete Delta Lake Architecture, its benefits, and how to implement & tune it for performance
- Deploy and manage Databricks SQL Warehouses with parameterized queries, alerts, and query caching
- Build streaming pipelines using Streaming Tables, Materialized Views, and Lakeflow Declarative Pipelines
- Implement Slowly Changing Dimensions (SCDs) and add Data Quality checks using Delta Live Tables
- Master Lakeflow Jobs to orchestrate your ETL pipelines like a pro
- Understand and apply Row-Level Security, Data Masking, and Delta Sharing for secure data access
- Learn Data Versioning, Time Travel, ZORDERING, Cloning, and Liquid Clustering
Skills covered in this course
Reviews
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SSam Adhikari
cool but it would be more nice if each module does not have any dependecy in the source files.
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YYuko Fujiwara
The instructor's enthusiasm was fantastic, and he delved deeply into the background and reasons behind his explanations, which helped me to understand the concepts more deeply. The course was 18.5 hours long, but as the name "boot camp" suggests, it had a lot of practical content, so it ended up taking an extra week, including the New Year holidays. As a non-native speaker, it was really difficult for me to keep up with the fast-paced English. However, I think it was worth it.
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PPankaj Shukla
Hello Ansh, you did excellent job and covered all aspects right from concepts to scenario based demo.
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AAnooshaKokula
Ansh Lamba’s teaching style is incredibly energetic and engaging, making it easy to follow every concept step-by-step. His course, combined with hands-on practice, builds strong confidence for the Databricks Associate level exam. After completing the course and practicing with Udemy tests to understand the exam pattern, I successfully cleared the certification. Thank you, Ansh Lamba!