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Databricks Certified Associate Developer for Apache Spark training and exam prep - master Spark architecture and the DataFrame API in Python or Scala, with hands-on labs.
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The Databricks Certified Associate Developer for Apache Spark is a developer-focused, associate-level certification. It validates that you understand Apache Spark architecture and can use the Spark DataFrame API to complete data-manipulation tasks - selecting and transforming columns, filtering and aggregating rows, joins, handling missing data, schemas, partitioning, UDFs and Spark SQL functions. The certification is earned by passing a single exam: 60 multiple-choice questions in about 90 minutes, taken online with remote proctoring, for about US$200. You can prepare and answer referencing Python (PySpark) or Scala. The exam also covers Spark architecture concepts (execution modes, lazy evaluation, transformations vs actions, shuffling, broadcasting, fault tolerance) and, in its current version, Structured Streaming and Spark Connect.
Apache Spark is one of the most important technologies in big data, and it underpins the Databricks platform. This certification proves you can write real Spark code - using the DataFrame API to transform, join and aggregate data at scale, and understanding how Spark executes under the hood. It is a practical, code-focused credential that signals genuine developer ability, and it complements platform-focused certifications like the Data Engineer Associate.
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This certification has no formal prerequisites and suits anyone who writes or wants to write Spark code. It is ideal for: - Python (PySpark) and Scala developers - Data engineers who work with Spark - Big data and analytics engineers - Anyone who wants to prove Spark DataFrame API skills Databricks recommends Python or Scala knowledge and about 6 months using the Spark DataFrame API, though nothing is formally required.
How to earn it:
1. Prepare with an Apache Spark Developer Associate exam-prep course that includes hands-on coding labs - that is what we provide.
2. Register for the exam through Databricks' official certification platform. Choose your language (Python or Scala) at registrati...
The Databricks Certified Associate Developer for Apache Spark certification validates your ability to develop and work with data processing solutions using Apache Spark and Databricks technologies. The exam assesses your knowledge of Spark architecture, DataFrames, Spark SQL, data transformations, data manipulation, performance considerations, and practical application of Spark for large-scale data processing. Understanding the exam structure and certification requirements can help you plan your preparation effectively and build confidence before the assessment. This section explains the exam pattern, question format, duration, certification requirements, and other important details you should know before taking the Databricks Certified Associate Developer for Apache Spark exam.
Exam details verified on 16 August 2026. The Databricks Certified Associate Developer for Apache Spark is earned by passing a single online- proctored exam of 60 multiple-choice questions in about 90 minutes, for about US$200 (plus applicable local taxes). You may reference Python (PySpark) or Scala. A passing score of 70% is commonly cited, though Databricks may use criterion-based scoring - confirm on Databricks' exam guide. The certification is valid for 2 years and is renewed by re-taking the current version of the exam. The current exam includes Structured Streaming and Spark Connect.
The Apache Spark Developer Associate is ideal for: - Python (PySpark) and Scala developers - Data engineers who write Spark code - Big data and analytics engineers There are no formal prerequisites. Python or Scala knowledge and some Spark experience help. If you want a broader, platform-focused data engineering credential (pipelines, Delta Lake, governance), the Databricks Data Engineer Associate may suit you - and the two complement each other well.
