The Databricks Certified Context Engineer Associate certification is one of the newest certifications in the Databricks certification portfolio and focuses on designing, assembling and governing the context used by AI agent systems.

I took the beta version of this exam during Data + AI Summit 2026, and this session will share what I learned from preparing for and taking it, along with an updated look at the current public exam.

We will walk through what to study, where to spend your preparation time, which Databricks services you should understand, and how to approach the scenario-based questions.

The current exam covers seven areas: Foundations of Context Engineering, System Prompt and Instruction Design, Knowledge Retrieval and Genie Configuration, Memory Architecture with Lakebase and MLflow, Tool Design and MCP, Context Compression, and Multi-Agent/Long-Horizon Task Design. Databricks

We will also leave time for an open Databricks Certification Q&A covering preparation strategies, study resources, exam-day questions and other Databricks certifications.

This is a community learning session. We will discuss concepts and practice-style questions, not confidential or live certification exam questions.

What we will cover

• What the Context Engineer Associate certification actually tests

• How I would prepare for the exam today

• The seven exam domains and where to focus

• Context failure modes: poisoning, distraction, confusion and clash

• Prompt and instruction design

• RAG, Databricks AI Search and retrieval strategies

• Genie configuration and trusted business context

• Lakebase and MLflow for agent memory

• MCP, tools and Agent Skills

• Context trimming, compression and compaction

• Multi-agent and long-running agent workflows

• Unity Catalog governance, metadata, PII and policy

• How to approach long scenario-based questions

• Practice-style questions and reasoning

• Open Q&A on Databricks certifications

The official exam guide currently weights Knowledge Retrieval and Genie Configuration at 20%, Memory Architecture with Lakebase and MLflow at 18%, and Foundations of Context Engineering at 16%, so I would give those areas slightly more time in the session. Databricks

90-minute agenda

5:00 to 5:10 PM
Welcome + Databricks certification updates

5:10 to 5:30 PM
Context Engineer Associate: exam structure and what to study

5:30 to 6:00 PM
Deep dive: retrieval, memory, MCP, context management, governance and multi-agent design

6:00 to 6:15 PM
Practice-style certification questions and how to reason through them

6:15 to 6:30 PM
Open certification Q&A

Resources:

• Agentic Systems: Deploy and Evaluate RAG Apps with Databricks AI

• official guide

• announcement,

• Databricks docs on authoring/deploying agents on Databricks Apps

• MCP: Advancing your agentic AI with MCP - A travel planning use-case on Databricks

• MLflow eval / AgentOps: From Traces to Evaluation: An Autonomous MLflow Agent Harness for AI AgentOps

• Vector Search / ACL: Mastering RAG Chatbot Security: ACL and Metadata Filtering with Mosaic AI Vector Search.