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Databricks Certified Context Engineer Associate

A new exam on what agents are given at inference time: prompts, retrieval, memory, MCP tools and context window management on Databricks.

What it signals

Practical assessment: Scenario-based multiple choice. Proctored multiple-choice, scenario-based.
Identity assurance: Proctored with identity verification. Proctored; online proctored or test centre. No test aides.
Depth: Associate. Associate level.
Experience expected: Under 6 months. Provider recommends 6+ months experience.
Portability: Mixed. Context-engineering concepts transfer, but scenarios are framed around Databricks products.
Verifiability: Public badge or registry. Public Accredible badge via credentials.databricks.com.

For hiring managers

Brand-new certification (live since late July 2026), so very few holders exist and there is no track record yet. Entirely agent/context focused and heavily tied to Databricks products (Genie, Lakebase, Unity Catalog, Agent Bricks).

Verifying it

Digital badge issued via Accredible at credentials.databricks.com (shareable URL an employer can open); holders may also opt in to the Databricks Certified Directory.

What it covers

Published exam outline

Foundations of Context Engineering 16%
System Prompt and Instruction Design 9%
Knowledge Retrieval and Genie Configuration 20%
Memory Architecture with Lakebase and MLflow 18%
Tool Design, MCP, and Agent Context 13%
Context Compression and Compaction 11%
Multi-Agent and Long-Horizon Task Design 13%

By topic

GenAI apps: Substantial (20 to 35%). System prompts 9% and retrieval 20% are classic GenAI-app topics (about 29%).
Agents: Core focus (over 35%). The whole exam concerns agent context; memory, tools/MCP, compaction and multi-agent design alone total 55%.
Classical ML: Not covered. No ML training content.
Operations: Touched on (under 10%). Only incidental evaluation/operations content.
Data: Touched on (under 10%). Data quality/metadata curation appears inside the retrieval section only.
Responsible AI: Touched on (under 10%). PII handling and policy enforcement via Unity Catalog are mentioned but not separately weighted.

Exam details

Who the provider says it is for. People who design, assemble and govern the information AI agent systems receive at inference time on Databricks (prompts, retrieval, memory, MCP tools, context window management).

Format: Multiple choice / multiple selection (approximately 45 scored; unscored items may be added)
Delivery: Proctored; online proctored or test centre. No test aides.
Code or hands-on work: Official page: all code in the exam is Python (SQL possible for data manipulation). Code is read in multiple-choice items; no labs.
Prerequisites: None
Recommended experience: 6+ months hands-on experience with context engineering tasks; related training recommended
Renewal: Retake the full current exam every 2 years

Preparing

Not confirmed

These details were not available from an official source at the time of research.

passingScore (not published)
Whether the exam was preceded by a beta period
Responsible-AI/governance share (governance objectives are embedded in sections, no separate weight)

Sources (4)