---
url: "https://xcademia.com/courses/databricks-data-engineer-associate-training"
title: Databricks Data Engineer Associate Training
description: " Learn Databricks, Spark, and Delta Lake in this 4-day mentor-led course aligned with the Data Engineer Associate certification. Build real ETL pipelines."
publishedAt: "2026-03-23T04:34:43.611342+00:00"
updatedAt: "2026-03-30T22:50:53.7265+00:00"
type: course
code: "AID-0087"
level: Practitioner
duration_days: "4"
track: "Data Engineering & Warehousing"
category: "AI, Data & Analytics"
credential_tier: tier1
price_gbp: "2199"
---

# Databricks Data Engineer Associate Training

> Build practical data engineering skills using Apache Spark, Delta Lake, and Databricks in real-world scenarios. Prepare for the Databricks Data Engineer Associate exam with mentor-led, hands-on learning.

## Overview

The Databricks Data Engineer Associate Training is a mentor-led, hands-on programme designed to equip professionals with the practical skills required to build and manage modern data pipelines using the Databricks Lakehouse Platform. The course is aligned with the Databricks Data Engineer Associate certification and focuses on real-world implementation using Apache Spark and Delta Lake.

Participants will work through practical scenarios covering data ingestion, transformation, optimisation, and orchestration. The programme emphasises building reliable and scalable ETL pipelines, managing structured and semi-structured data, and applying best practices in data engineering workflows.

By the end of the course, learners will be able to confidently design and deploy data pipelines within Databricks, understand data governance with Unity Catalog, and apply performance tuning techniques. This course supports both certification preparation and real-world job readiness.

## Prerequisites

- Basic Python or SQL knowledge
- Familiarity with data concepts
- Understanding of cloud fundamentals

## What you will learn

- Design scalable data pipelines in Databricks
- Analyse Spark jobs and optimise performance
- Implement Delta Lake for reliable data storage
- Evaluate ETL architectures and workflows
- Communicate data engineering solutions effectively
- Lead data pipeline development initiatives

## Skills you will gain

- Spark DataFrame transformations
- Delta Lake operations
- ETL pipeline design
- Workflow orchestration basics
- Data governance principles
- Performance optimisation techniques

## Career progression

- Data Engineer
- Analytics Engineer
- Big Data Developer
- Data Platform Enginee

## Curriculum

1. **Module 1: Databricks Platform Fundamentals**
   - Lakehouse architecture overview
   - Databricks workspace and clusters
   - Notebooks and workflows
   - Data formats and storage layers
2. **Module 2: Apache Spark for Data Engineering**
   - Spark DataFrames and transformations
   - Lazy evaluation and execution plans
   - Working with structured and semi-structured data
   - Spark SQL fundamentals
3. **Module 3: Delta Lake & Data Management**
   - Delta Lake architecture and features
   - ACID transactions and versioning
   - Schema enforcement and evolution
   - Time travel and optimisation
4. **Module 4:  ETL Pipelines & Orchestration**
   - Designing ETL pipelines
   - Batch and streaming ingestion
   - Workflow orchestration with jobs
   - Error handling and monitoring
5. **Module 5: Data Governance with Unity Catalog**
   - Data governance concepts
   - Managing access controls
   - Data lineage and auditing
   - Secure data sharing practices
6. **Module 6: Performance Optimisation & Best Practices**
   - Query optimisation techniques
   - Partitioning and indexing strategies
   - Caching and tuning clusters
   - Cost optimisation strategies
7. **Module 7: Exam Preparation & Practice Scenarios**
   - Exam structure and domains
   - Practice questions and scenarios
   - Common pitfalls and strategies
   - Final readiness assessment

## Exam & certification

## Delivery options

- **Live Online** — Join live instructor-led sessions from anywhere. Interactive, engaging, and flexible.
- **Onsite Training** — We come to you. Training delivered at your workplace for teams of 6 or more.
- **Venue-Based** — Classroom training at a professional venue. Ideal for focused, immersive learning.
- **Blended** — Combine online and in-person learning for maximum flexibility and impact.

## Frequently asked questions

**Is this course suitable for beginners?**

It is best suited for those with basic programming or data knowledge.



**Will I get hands-on practice?**

Yes, the course includes labs and practical scenarios throughout.



**Does this include exam preparation?**

Yes, it includes targeted preparation aligned with the certification objectives.

**Do I need prior Spark experience?**

No, Spark fundamentals are covered from the ground up.

**Will I receive a certificate?**

Yes, you will receive a Certificate of Completion after finishing the course.

## Course at a glance

| Field | Value |
| --- | --- |
| Code | AID-0087 |
| Duration | 4 days |
| Level | Practitioner |
| Track | Data Engineering & Warehousing |
| Category | AI, Data & Analytics |
| Credential tier | tier1 |
| Price (GBP) | £2199 |

---

## About this content

This Markdown course profile is the citation-grade twin of [Databricks Data Engineer Associate Training](https://xcademia.com/courses/databricks-data-engineer-associate-training). It is published by **Xcademia** (UK Companies House 12322710) and is available for AI search engines and large language models to index, summarise, and cite.

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