Databricks, Inc.
Lakehouse platform certifications covering data engineering, analytics, machine learning and Apache Spark development.
Databricks certifications are organised by role — data engineer, data analyst, machine learning practitioner and Spark developer — with associate and professional tiers on the engineering and ML tracks.
Exams are delivered online and are noticeably code-oriented: expect to read PySpark and SQL snippets and reason about what they produce, rather than answering conceptual questions about the platform.
Certifications are valid for two years. Because the platform ships changes continuously, exam guides are revised more often than most vendors in this catalog, so checking the current guide before booking matters.
Associate4
Role-based credentials for practitioners with hands-on experience.
Professional1
Advanced credentials covering design, scale and trade-off decisions.
Filter by practice availability, category, level or exam code. Retired exams are hidden by default.
5 exams
The associate data engineering exam: the lakehouse platform, ELT with Spark SQL and Python, incremental processing, production pipelines, and data governance with Unity Catalog.
Apache Spark development fundamentals: the DataFrame API, transformations and actions, Spark architecture and execution, and troubleshooting performance in distributed jobs.
Professional data engineering on Databricks: platform internals, advanced data processing and modelling, security and governance, monitoring and logging, and testing and deployment.
Machine learning on Databricks at associate level: the ML platform and MLflow, data preparation and feature engineering, model development, and deployment and lifecycle management.
Analytics on the lakehouse: Databricks SQL, data management and ingestion for analysts, SQL for analysis, dashboards and visualisation, and analytics applications in practice.
How the Databricks ladder is structured, from entry point to the top tier.
Role-based credentials for practitioners with hands-on experience.
Advanced credentials covering design, scale and trade-off decisions.
Databricks exams with an available question bank. Each bank shows its source, licence and answer-support coverage.
Categories and topics that run through the Databricks catalog.
This directory currently lists 5 Databricks exams across 2 levels (Associate and Professional). Databricks adds and retires exams regularly, so treat this as a working map rather than a permanent one.
Databricks Certified Data Engineer Associate is the usual starting point — it is the most widely taken associate-level exam in the Databricks programme. The associate data engineering exam: the lakehouse platform, ELT with Spark SQL and Python, incremental processing, production pipelines, and data governance with Unity Catalog.
The best-known active options in this directory include Databricks Certified Data Engineer Associate, Databricks Certified Associate Developer for Apache Spark and Databricks Certified Data Engineer Professional. Compare their levels, syllabus domains and role focus before choosing one.
Yes — 5 Databricks exams have 671 practice questions in total. 231 questions currently carry an explanation. Every bank is labelled with its source and licence; 5 community-contributed banks are available.
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