Analytics Engineer
Real portfolio pieces built during the course, not a certificate for its own sake. Each one is work you can show.
- Metric definition recordA disputed metric settled: the two figures reconciled exactly, the owner named, the definition written once in a tested model, a separately named measure for the other team, and every dashboard reading the model.
- Test failure reportThree failing data tests on a new orders model, each traced to the data, the model or the test's assumption, with a fix that keeps every real sale and the test left switched on.
- Incremental model designA design to make a slow model fast without losing late changes: processing changed rows within a lookback that covers the returns window, a weekend full rebuild compared with the nightly result, and a way to roll back.
- Release note and documentationA week's release note and the documentation that goes with it: each change in plain words, what the business can now rely on and who owns it, what is not ready yet, and how a requested change was handled safely.
What you'll learn
Course content · 7 modules, 20 lessons
Sign up to unlock every lesson - the titles below show exactly what is inside.
Where analytics engineering sits, what a data model is, how tests work, and why one definition per metric matters.
Requirements
- No prior experience in this field is required to start.
- A computer with a reliable internet connection.
- Comfortable using a web browser - no software to install.
Description
Every CertClue course follows the same seven-part shape: fundamentals, the role translated out of job-posting language, a real working day, the job's recurring rhythms, a multi-day simulation, the portfolio you build along the way, and a handoff into your next move. Here is what that looks like for analytics engineer.
Who this course is for
Anyone aiming to become a analytics engineer, including career changers with no background in it yet. This is the entry rung of a realistic ladder:
Turns raw data into tested, documented models that analysts and dashboards use, and owns the definitions of the metrics built on them.
Designs how the organisation's data is modelled, keeps it fast and affordable as it grows, and sets the standards other analytics engineers follow.
Leads the data team, decides what gets modelled and measured, and answers for whether the business can trust its numbers.
Where it leads
This course prepares you for the dbt Analytics Engineering Certification role or credential path. Named for preparation only - no partnership or endorsement is implied.
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