Program Outline
Advanced Data Engineering with Databricks
This advanced program aligns to the Databricks Certified Data Engineer Professional path and focuses on production-scale engineering decisions. Teams work through streaming patterns, privacy-aware data design, performance tuning, and deployment automation practices that matter when Databricks is part of a broader enterprise platform.
Certification
Databricks Certified Data Engineer Professional
Delivery
Virtual, On-site, or Hybrid
Duration
3 days
Product
Databricks Data Intelligence Platform
Role
Data Engineer
Databricks
Advanced Data EngineeringStreaming, optimization, asset bundles
Databricks
Best Fit
Audience Profile
Who This Program Is For
Designed for experienced practitioners who need to implement advanced data engineering patterns on Databricks across streaming, privacy, optimization, and deployment automation.
Overview
Program Summary
Advanced Databricks engineering program aligned to professional-level data engineering capabilities across streaming, privacy, optimization, and asset-bundle deployment practices.
Program Outcomes
After this program, participants will be able to...
Design advanced streaming and declarative pipeline strategies
Improve privacy, governance, and secure data handling decisions
Tune Databricks workloads for performance and operational efficiency
Deploy platform assets more consistently with Databricks Asset Bundles
Delivery Formats
Enterprise Suitability
Course Outline
Complete Module Sequence
Review the full module sequence for this program, including the primary topic coverage in each module where available.
1Module 1
Streaming and declarative pipeline design
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Module 1
Streaming and declarative pipeline design
Advance from batch-oriented engineering into streaming and continuously managed data pipelines using Databricks-native capabilities for scalable operations.
- Databricks Streaming and Delta Live Tables
2Module 2
Privacy-aware data engineering practices
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Module 2
Privacy-aware data engineering practices
Address sensitive data handling, access separation, and governance considerations for enterprise data products and regulated environments.
- Databricks Data Privacy
3Module 3
Performance engineering on the Databricks platform
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Module 3
Performance engineering on the Databricks platform
Improve workload speed, cost efficiency, and runtime behavior by applying proven Databricks performance optimization patterns.
- Databricks Performance Optimization
4Module 4
Deployment automation for production platforms
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Module 4
Deployment automation for production platforms
Package and promote Databricks assets more consistently across environments using asset bundles and disciplined deployment workflows.
- Automated Deployment with Databricks Asset Bundles
Coverage Areas
Topic Coverage
Coverage Item 1
Databricks Streaming and Delta Live Tables
Coverage Item 2
Databricks Data Privacy
Coverage Item 3
Databricks Performance Optimization
Coverage Item 4
Automated Deployment with Databricks Asset Bundles
Customization
Adapt This Program for Your Team
We can adapt this program around your team structure, platform priorities, delivery goals, and the scenarios your people need to work through in practice.
- •Emphasize performance tuning for your largest workload patterns
- •Add privacy and regulated-data handling use cases
- •Extend with CI/CD and platform promotion workflows for Databricks asset bundles
