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DataAdvancedDatabricks Data Intelligence PlatformAdvanced Data Engineering

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.

Role-Based Certification PrepTrack: Databricks Certified Data Engineer ProfessionalOfficial Source: Databricks

Certification

Databricks Certified Data Engineer Professional

Delivery

Virtual, On-site, or Hybrid

Duration

3 days

Product

Databricks Data Intelligence Platform

Role

Data Engineer

Lab-Based DeliveryCustomizable for TeamsOfficially Aligned: Databricks
Priority Program

Best Fit

Data EngineerAdvanced Data EngineeringCertification ReadinessTailored Team Delivery

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.

Course Outline

Complete Module Sequence

Review the full module sequence for this program, including the primary topic coverage in each module where available.

1

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
2

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
3

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
4

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
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