Data Engineering with Databricks
Build scalable data pipelines and ETL workflows on the Databricks platform
Course Overview
This comprehensive Data Engineering with Databricks course is designed for data professionals who want to build robust, scalable data pipelines using the Databricks platform. You'll learn to design and implement end-to-end data engineering solutions that handle large-scale data processing workloads.
The course covers advanced topics including Delta Live Tables for declarative pipeline development, streaming data processing, data quality monitoring, and performance optimization techniques. Participants will gain hands-on experience with real-world data engineering scenarios and best practices.
Through practical exercises, you'll master the tools and techniques needed to transform raw data into analytics-ready datasets, implement data governance, and maintain production-grade data pipelines at enterprise scale.
Key Learning Outcomes
- Design and implement scalable ETL/ELT pipelines
- Master Delta Live Tables for pipeline orchestration
- Process streaming data with Structured Streaming
- Implement data quality checks and monitoring
- Optimize pipeline performance and troubleshoot issues
- Apply data governance and security practices
Course Details
Duration
4 Days (32 hours)
Format
Live MCT-led online delivery with intensive hands-on labs
Target Audience
Data engineers, ETL developers, data architects, and senior data analysts
Prerequisites
Experience with SQL, Python/Scala, and basic understanding of distributed computing concepts
Pricing
$1,995 USD
Live online · MCT-led
Why Train with Instrovate
Official Databricks Partner
Certified partner with access to latest training materials and best practices
Expert MCT Instructors
Learn from Microsoft Certified Trainers with real-world experience
Hands-on Labs
Practical experience with live Databricks environments and datasets
8+ Years Experience
Proven track record of global training excellence and student success