Databricks Certified Data Engineer Associate

Databricks · DATABRICKS-DEA · Associate

Databricks · Databricks Ecosystem

Databricks Certified Data Engineer Associate

DATABRICKS-DEAactiveAssociate
Official Databricks source · databricks.com

DATABRICKS-DEA · ● Active · Associate · Databricks

Self-paced online proctored exam validating core competency in Databricks Lakehouse Platform, Apache Spark-based ELT, incremental data processing, production pipelines, and data governance. Target role: Data Engineer, Big Data Engineer, or Analytics Engineer working with Databricks platform.


Exam facts

FieldValue
Cost$200 USD
Duration90 minutes
Questions45 (all scored)
Passing score~70% (equivalent score 63 out of 90)
FormatMultiple choice + multiple response
DeliveryWebassessor online proctored (remote, proctor-supervised)
LanguagesEnglish
Valid3 years from pass date
RenewalRetake exam or maintain by earning points via approved learning paths
PrerequisitesNone (but intermediate SQL + Python strongly recommended)
Released2021 (current format active 2024)
RetiringN/A — active and regularly updated

Vendor source — Databricks Certification ↗
Official exam guide — Databricks Certified Data Engineer Associate Study Guide ↗
Exam objectives — Data Engineer Associate Exam Objectives ↗


About

The Databricks Certified Data Engineer Associate credential validates hands-on proficiency with the Databricks Lakehouse Platform and Apache Spark—specifically in building, deploying, and maintaining data pipelines in production. Launched in 2021 and updated in 2024, this exam targets mid-level practitioners transitioning into or solidifying roles as data engineers working with Delta Lake, Databricks SQL, and Spark-based ETL/ELT workflows. It is the foundation credential in Databricks' data engineering stack and a prerequisite pathway for the Professional-level and Generative AI Engineer certifications.


Domain context — Data/AI

Data engineering foundations and cloud-native big data platforms. Covers distributed data processing, lakehouse architecture, incremental transformations, data quality, and governance.

Read full deep dive — Databricks Ecosystem →


Topics covered

The exam blueprint weights five core domains:

  • Databricks Lakehouse Platform (~24%) — Unity Catalog, workspace fundamentals, compute concepts, cluster types, SQL Endpoints, Jobs, Data Explorer
  • ELT with Apache Spark (~29%) — DataFrames, SQL transformations, PySpark fundamentals, Delta Lake format, schema inference, write modes (append, overwrite, merge)
  • Incremental Data Processing (~22%) — Structured Streaming, Change Data Feed, medallion architecture (Bronze/Silver/Gold), incremental data loading patterns
  • Production Pipelines (~16%) — Databricks Workflows (Jobs), scheduling, error handling, monitoring, orchestration, MLflow integration
  • Data Governance (~9%) — Unity Catalog, data lineage, access controls, data quality, PII handling, audit logs

Source: Databricks Certified Data Engineer Associate Objectives ↗


Common skills at Data/AI · Associate

Shared foundational competencies for data/analytics roles at Associate level.

  • SQL query writing and optimization (SELECT, JOIN, aggregation, window functions, CTEs)
  • Python scripting for data processing and automation
  • Familiarity with relational and semi-structured data schemas
  • Understanding of ETL vs. ELT paradigm and when to apply each
  • Basic distributed computing concepts (partitioning, shuffling, parallelism)
  • Data quality validation and testing practices
  • Logging, monitoring, and debugging data pipelines
  • Version control (Git) for pipeline code

Recommended courses at Data/AI · Associate

ProviderTitleCostURL
Databricks Academy (Official)Data Engineer Associate Certification PrepFree
Udemy (Derar Alhussein)Databricks Certified Data Engineer Associate - Preparation$12–$50
PluralsightDatabricks Data Engineer Path$299/yr
A Cloud GuruDatabricks Data Engineer Associate$49/mo
YouTube (Databricks Official)Databricks Learning PlaylistFree

Course-selection rule: The Databricks Academy official prep course is free and authoritative. Alhussein's Udemy course is widely cited as the best structured independent preparation. Pluralsight and A Cloud Guru offer path-based curricula covering breadth.


Practice exams

ProviderTitleCostURL
Udemy (Derar Alhussein)Databricks Certified Data Engineer Associate Practice Exams$15–$30
WhizlabsDatabricks Certified Data Engineer Associate Practice Tests$20
Databricks AcademyOfficial Practice ExamFree (limited attempts)

Books

TitleAuthorPublisherYearISBNURL
Databricks Lakehouse Platform CookbookRui QiuPackt Publishing2023978-1835463079
Learning Spark (2nd ed.)Jules S. Damji, Brooke Wenig, Tathagata Das, Denny LeeO'Reilly2020978-1492041659
Spark: The Definitive GuideBill Chambers, Matei ZahariaO'Reilly2018978-1491912219
Delta Lake Up and RunningBennie HagedornO'Reilly2024978-1098139155

Book rule: The Databricks Lakehouse Cookbook directly targets the platform and topics on the exam. Learning Spark and Spark: The Definitive Guide are foundational Apache Spark references that cover 70%+ of the ELT exam content. Delta Lake Up and Running (2024) is current and covers incremental processing and lakehouse patterns.


Typical job titles at Data/AI · Associate

Data Engineer · Big Data Engineer · Lakehouse Engineer · Analytics Engineer (Databricks) · Data Platform Engineer (Databricks-focused) · ETL Developer (Apache Spark / Databricks)

(Job titles drawn from Databricks job board, LinkedIn, and major data engineering job postings listing this cert as required or preferred.)


Salary

Salary rule: Ranges reflect typical Data Engineer roles where Databricks certification is listed as required or preferred. Regional variations account for cost-of-living and local demand; USD figures are mid-market enterprise data engineering roles with 2–4 years experience post-Associate certification.


Skills validated

Specific technical competencies tested by this exam.

  • Databricks Workspace & Compute Management — cluster configuration, compute pools, SQL Endpoints, workspace organization
  • Apache Spark SQL & DataFrames — transformations, actions, query optimization, caching strategies
  • PySpark Programming — RDD/DataFrame/Dataset APIs, UDF creation, performance tuning
  • Delta Lake — ACID transactions, table formats, schema evolution, time-travel, Z-Order optimization
  • Structured Streaming — continuous processing, stateful operations, trigger modes, watermarking
  • Change Data Feed (CDF) — incremental data capture and processing patterns
  • Medallion Architecture — Bronze/Silver/Gold layer design, data quality checks, incremental loads
  • Databricks SQL — SQL Endpoints, SQL queries, parameterized queries, dashboards
  • Databricks Workflows — job scheduling, multi-task pipelines, error handling, notification integration
  • Unity Catalog — metastore setup, table access control, lineage tracking
  • Data Governance — PII masking, audit logging, compliance patterns in Databricks

Related certifications

  • Stacks with: [Databricks Certified Data Analyst ↗]({file not yet created})
  • Prerequisite for: [Databricks Certified Data Engineer Professional ↗]({file not yet created})
  • Prerequisite for: [Databricks Certified Generative AI Engineer Associate ↗]({file not yet created})
  • Common path: Complete DEA → Professional → Generative AI Engineer for full Databricks data/ML stack
  • Equivalents at this level: [AWS Certified Data Analytics - Specialty ↗]({file not yet created}) (broader AWS analytics) · [Google Cloud Certified Associate Cloud Engineer ↗]({file not yet created}) (broader cloud platform)
  • Vendor overview: Databricks Vendor Overview ↗

Sources


Last verified: 2026-05-01
Parent ecosystem: Databricks Ecosystem
Parent domain: Data/AI Domain
Vendor overview: Databricks Vendor Overview

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