---
url: "https://xcademia.com/courses/dbt-analytics-engineering"
title: dbt Analytics Engineering
description: "Learn dbt analytics engineering with hands-on ELT pipelines, testing, documentation, and lineage tracking in a 2-day practical course."
publishedAt: "2026-03-17T09:46:05.199332+00:00"
updatedAt: "2026-03-30T22:50:53.7265+00:00"
type: course
code: "AID-0043"
level: Practitioner
duration_days: "2"
track: "Data Engineering & Warehousing"
category: "AI, Data & Analytics"
credential_tier: tier1
price_gbp: "1799"
---

# dbt Analytics Engineering

> Learn modern analytics engineering with dbt through mentor-led sessions and practical scenarios. Build tested, documented, and production-ready ELT pipelines using real-world workflows.

## Overview

This mentor-led dbt Analytics Engineering programme focuses on building reliable, maintainable, and scalable data transformation workflows using modern ELT practices. Learners explore how dbt enables analytics teams to take ownership of data modelling, testing, and documentation within cloud data platforms.

Through practical scenarios, participants implement modular SQL transformations, apply testing frameworks, and generate automated documentation. The course emphasises version control, collaboration workflows, and lineage tracking, ensuring transparency and trust in data pipelines.

By the end of the programme, learners will be able to design and manage dbt projects, enforce data quality, and maintain clear lineage across transformations. The course is aligned with modern analytics engineering practices used across high-performing data teams.

## Prerequisites

- Basic knowledge of SQL
- Understanding of data pipelines or data analysis
- Familiarity with data warehouses helpful

## What you will learn

- Build and manage ELT pipelines using dbt
- Design modular and scalable data models
- Implement data testing and validation
- Generate documentation and track lineage
- Deploy dbt workflows in production environments
- Apply best practices for analytics engineering

## Skills you will gain

- dbt project development
- ELT pipeline design
- Data modelling and transformation
- Data testing and validation
- Data lineage and documentation
- Analytics engineering workflows
- CI/CD for data pipelines

## Career progression

- Analytics Engineer
- Data Engineer
- BI Engineer
- Data Analyst (Advanced)
- Data Platform Engineer

## Curriculum

1. **Module 1**
2. **Module 2**
3. **Module 3**
4. **Module 4**

## 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

**1. What is dbt?**

dbt (data build tool) is a framework for transforming data in warehouses using SQL-based workflows.



**2. What is ELT?**

ELT stands for Extract, Load, Transform, where data is transformed inside the data warehouse.



**3. Is this course hands-on?**

Yes. Participants build dbt models, tests, and documentation.



**4. Why is data testing important?**

It ensures data reliability and accuracy for analytics and decision-making.



**5. What roles benefit from this course?**

Analytics engineers, data engineers, BI professionals, and advanced analysts.

## Course at a glance

| Field | Value |
| --- | --- |
| Code | AID-0043 |
| Duration | 2 days |
| Level | Practitioner |
| Track | Data Engineering & Warehousing |
| Category | AI, Data & Analytics |
| Credential tier | tier1 |
| Price (GBP) | £1799 |

---

## About this content

This Markdown course profile is the citation-grade twin of [dbt Analytics Engineering](https://xcademia.com/courses/dbt-analytics-engineering). 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.

When citing or quoting, please attribute *Xcademia* and link back to the source URL above.

- Source: https://xcademia.com/courses/dbt-analytics-engineering
- Publisher: Xcademia — https://xcademia.com
- Catalogue index: https://xcademia.com/llms-full.txt