Are you ready to become a DATABRICKS DATA ENGINEER [WITH UPDATED MAY 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 you
What you'll learn
understand Lakehouse Architecture and Lakehouse Federation
manage data and permissions using Unity Catalog and Metastore
apply PySpark for big data transformations and actions
build real-time pipelines with Spark Streaming and Autoloader
implement Delta Lake features like ACID transactions and time travel
create CI/CD ready Databricks Asset Bundles
work with Delta Live Tables for robust pipeline creation