Databricks Certified Professional Data Engineer Course


Databricks Certified Professional Data Engineer Course

Here’s a breakdown of the Databricks Certified Professional Data Engineer course:

What is the Databricks Certified Professional Data Engineer Course?

  • Certification for Expertise:  The Databricks Certified Professional Data Engineer certification validates your proficiency in advanced data engineering tasks on the Databricks platform.
  • Focus: It demonstrates your deep understanding of Databricks tools (Apache Spark™, Delta Lake, MLflow, Databricks CLI, REST API), building optimized and cleaned ETL pipelines, and data modeling for a lakehouse architecture.
  • Prestige: This certification is a strong addition to your resume, showing potential employers your skills in working with a powerful big data processing and analytics platform.

Prerequisites and Preparation

    • No Formal Prerequisites: Although there are none, Databricks strongly recommends these:At least one year of hands-on data engineering experience.
    • Databricks’ recommended training courses (these can be found on the Databricks website).
  • Exam Guide: Before the exam, thoroughly review the official Databricks exam guide which outlines all the topics you’ll be tested on.

Exam Details

  • Format: Proctored online exam with multiple-choice questions.
  • Questions: 60
  • Time Limit: 120 minutes
  • Languages: English
  • Validity: 2 years

Topics Covered

  • Databricks Lakehouse Platform: Deep understanding of the platform architecture, components, and how to navigate it.
  • Data Engineering with Apache Spark: Expertise in data transformations, data quality, performance optimization, and debugging using Spark.
  • Delta Lake:  Building reliable, scalable, and performant data pipelines with Delta Lake (transactions, time travel, etc.).
  • Productionizing Data Workflows: Scheduling, monitoring, error handling, and orchestration of production-level data pipelines.
  • MLflow: Knowledge of the MLflow framework for managing the machine learning lifecycle.
  • Security and Governance:  Implementing security best practices, governance models, and access control on the Databricks platform.

Benefits of Databricks Data Engineer Certification

  • Validate Expertise:  Demonstrates mastery of data engineering concepts specifically within the Databricks ecosystem.
  • Career Advancement: Opens doors to new opportunities and potentially higher salaries.
  • Enhanced Skillset: The preparation process itself helps strengthen your data engineering skills.
  • Recognition:  The certification badge acts as industry recognition of your specialized abilities

How to Prepare

  1. Databricks Academy Courses: Take advantage of the relevant courses and learning paths provided by Databricks.
  2. Hands-On Practice:  Engage in project-based work with Databricks to gain experience.
  3. Exam Guide: Use the official exam guide to understand the specific knowledge domains you’ll be tested on.
  4. Practice Exams (If Available): Look for resources that offer practice exams to simulate the real exam experience.

Databricks Training Demo Day 1 Video:

You can find more information about Databricks Training in this Dtabricks Docs Link



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