Databricks Certified Data Engineer Associate

I’ve been searching at taking the Databricks Data Engineer Associate Certification (the Databricks web page for the certification is here) as I’ve cited the certification covers areas such as the standard Databricks platform, Delta Lake and Delta Live Tables, the SQL endpoints, dashboarding, and orchestration – best for any work I would do in Databricks. The certification is concentrated on human beings who have up to 6 months trip working with Databricks. There is the Spark Developer certification however for humans like me who are Spark-light in phrases of skillset, it can appear pretty daunting.The certification covers areas such as the standard Databricks platform, Delta Lake and Delta Live Tables, the SQL endpoints, dashboarding, and orchestrationWhy do this exam? Well, I like the inclusion of Delta Lake which can be used in many engines…such as Serverless SQL Pools in Synapse Analytics. So being in a position to center of attention on how to work with Delta is very useful. There’s additionally Delta Live Tables too, a magnificent addition to the platform. I additionally like the Just Enough Python section, as I’m now not a great deal of a Python programmer however being given practise on applicable areas to pay attention on is very useful. Overall it offers a high-quality overview of the Databricks platform and maintains it very applicable to the Lakehouse pattern. Plus it’s now not heavy on the proper Spark implementation, very beneficial for humans like me!I additionally like to see the listing of competencies that are anticipated in the certification, this would possibly sound apparent however I like to recognize what a “Databricks Data Engineer” may want to recognize (at least at this degree of experience). E.G. if you prefer to work as an Azure Data Engineer, what capabilities may you need? What structures and elements ought to you use? The Microsoft DP-203 examination lists out all the predicted capabilities and systems and virtually offers you a focal point (and boundary) on what you want to comprehend – awesome for learning.Let’s dive into the examination important points and predicted capabilities for the Databricks Certified Data Engineer Associate. I won’t be supplying hyperlinks to mastering for every and each item, however as a substitute some ordinary sources to appear at.

Databricks Certified Data Engineer Associate

The Databricks Certified Data Engineer Associate certification exam assesses an individual’s ability to use the Databricks Lakehouse Platform to complete introductory data engineering tasks. This includes an understanding of the Lakehouse Platform and its workspace, its architecture, and its capabilities. It also assesses the ability to perform multi-hop architecture ETL tasks using Apache Spark SQL and Python in both batch and incrementally processed paradigms. Finally, the exam assesses the tester’s ability to put basic ETL pipelines and Databricks SQL queries and dashboards into production while maintaining entity permissions. Individuals who pass this certification exam can be expected to complete basic data engineering tasks using Databricks and its associated tools.

Minimally Qualified Candidate

The minimally qualified candidate should be able to:

  • Understand how to use and the benefits of using the Databricks Lakehouse Platform and its tools, including:
    • Data Lakehouse (architecture, descriptions, benefits)
    • Data Science and Engineering workspace (clusters, notebooks, data storage)
    • Delta Lake (general concepts, table management and manipulation, optimizations)
  • Build ETL pipelines using Apache Spark SQL and Python, including:
    • Relational entities (databases, tables, views)
    • ELT (creating tables, writing data to tables, cleaning data, combining and reshaping tables, SQL UDFs)
    • Python (facilitating Spark SQL with string manipulation and control flow, passing data between PySpark and Spark SQL)
  • Incrementally process data, including:
    • Structured Streaming (general concepts, triggers, watermarks)
    • Auto Loader (streaming reads)
    • Multi-hop Architecture (bronze-silver-gold, streaming applications)
    • Delta Live Tables (benefits and features)
  • Build production pipelines for data engineering applications and Databricks SQL queries and dashboards, including:
    • Jobs (scheduling, task orchestration, UI)
    • Dashboards (endpoints, scheduling, alerting, refreshing)
  • Understand and follow best security practices, including:
    • Unity Catalog (benefits and features)
    • Entity Permissions (team-based permissions, user-based permissions)


Testers will have 90 minutes to complete the certification exam.


There are 45 multiple-choice questions on the certification exam. The questions will be distributed by high-level topic in the following way:

  • Databricks Lakehouse Platform – 24% (11/45)
  • ELT with Spark SQL and Python – 29% (13/45)
  • Incremental Data Processing – 22% (10/45)
  • Production Pipelines – 16% (7/45)
  • Data Governance – 9% (4/45)


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