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Data Engineering

Databricks Certified Data Engineer Associate

Validates ability to use Databricks for data engineering workflows. Covers Delta Lake, Apache Spark, and data pipeline development on the Databricks platform.

Provider

Databricks

Level

Associate

Duration

1–3 months

Cost

$200

Passing Score

70%

Validity

2 years

Salary Impact

+$15,000–$25,000 avg

Prerequisites

Python or SQL proficiency

Spark fundamentals

Data engineering concepts

Exam Format

45 multiple-choice questions, 120 minutes, $200 USD

Exam Topics & Weights

Data lakes and delta lake

25%

ETL with Spark

30%

Databricks workspace and notebooks

20%

Production pipelines and governance

25%

8-Week Study Plan

Weeks 1

Focus: Databricks workspace and notebooks

Databricks documentation

Notebook best practices

Workspace setup

Weeks 2-3

Focus: Delta Lake and Lakehouse architecture

Delta Lake documentation

Lakehouse concepts

Time travel and versioning

Weeks 4-5

Focus: Apache Spark and PySpark

PySpark API reference

Distributed computing patterns

Performance tuning

Weeks 6-7

Focus: Data engineering pipelines and production

Databricks Jobs

Workflow orchestration

Quality and testing

Exam Tips & Strategies

Delta Lake ACID transactions and schema evolution are critical

Understand partitioning and bucketing for performance

Spark DataFrame API (not RDD API) is the focus

Data quality and error handling patterns are tested

Workflow orchestration and production considerations matter

Hands-on in Databricks Community Edition is essential

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