About Course
About dbt Analytics Engineering Certification Training
Turn warehouse SQL into tested, documented, version-controlled models with dbt, from source definitions to deployment jobs.
The habit dbt trains is refusing to ship a model nobody can trace. Every table has a declared source, a test that fails on exactly the wrong rows, an owner and a place in the dependency graph, so a changed column shows up as a list of downstream models instead of a surprise on a dashboard. The course works through the project layout, staging and mart layers, generic and singular tests, Jinja macros, incremental strategies, snapshots, exposures and documentation, then deploys the whole thing through dbt Cloud environments.
Course Overview
12-week dbt Analytics Engineering certification training (72 hours) on models, tests, macros, snapshots, Semantic Layer and dbt Cloud deployment.
Why Learn dbt Analytics Engineering Certification Training
Analytics teams in India are moving the reporting layer out of spreadsheets and ad-hoc warehouse scripts, and dbt is the tool they are standardising on. The certification is named in analytics engineering job descriptions because it proves the candidate can build a project, not just query one. It turns a modelling claim into a project you can open.
It changes what people ask you to build. Without the credential you inherit one folder of SQL and no tests; with it you are the person who lays out the layers, decides which model runs incrementally and puts a freshness check in place. You also get the vocabulary the role uses, so the first month on the job is shorter.
Who Should Join This Course
- SQL Analysts Writing Warehouse Queries — Turning ad-hoc SQL into a modelled, tested, reviewed project
- BI Developers — Owning the metrics layer that every dashboard quietly depends on
- Data Engineers Moving Into Modelling — Applying software engineering practice to transformation work
- Consultants Delivering Analytics Projects — Handing over a dbt project the client can maintain without you
- Team Leads Standardising Analytics Work — Setting the model layers, the naming rules and the review gate
- Fresh Graduate Trainees — Entering analytics engineering through a tools-first certification
Prerequisites
You need working SQL and a basic grasp of how a warehouse is modelled. dbt is a transformation tool that sits after extraction, so you should be comfortable answering "where does this number come from". No dbt experience is required.
Learning Objectives
- Lay out a dbt project with staging, intermediate and mart layers
- Declare sources with freshness and write schema and source tests
- Build models with ref and source and choose materialisation by cost
- Write generic and singular tests that fail on exactly the wrong rows
- Implement incremental models with the merge, delete+insert and insert strategies
- Track slow-changing history with a snapshot and read the check columns
- Publish exposures, documentation and a working column-level lineage graph
- Sit the timed dbt exam: 65 questions in two hours
Certification Objectives Covered
The syllabus follows the published dbt Analytics Engineering objectives: dbt Core, dbt Cloud, Jinja and Macros, Snapshots, dbt Semantic Layer, dbt Tests and Documentation, and the objective-to-topic map for the exam, the timed practice assessment and the exam-day plan.
Career Opportunities After This Programme
- Analytics Engineer
- Data Engineer
- BI Engineer
- Analytics Consultant
- Data Modelling Specialist
- Analytics Tech Lead
Hands-on Practice and Capstone
Capstone: You receive a raw sales and customer extract and a reporting deadline. You declare the sources with freshness, build a staging layer, an intermediate layer for reusable logic, and a mart a dashboard can read. You add generic and singular tests, convert the largest model to an incremental build, add a snapshot for the customer dimension, publish the documentation and lineage, then deploy through a dbt Cloud environment and run the full test suite.
Production scenario: A finance team has stopped trusting the revenue number on the executive dashboard, and the previous analyst left a spreadsheet of SQL with no tests. Decide how you rebuild the model, which tests you would insist on, whether the model should be incremental, and how you show the numbers changed before and after your work.
Course Duration, Mode and Certification
The course runs for 12 weeks (72 hours), three sessions a week of two hours each. Modes: Classroom / Live Online / Hybrid. Certificate issued: SkilBrill Course Completion Certificate. This programme prepares you for the dbt Analytics Engineering exam, which is booked and paid for with the vendor separately from the course fee.
Why Train at SkilBrill
SkilBrill Training Institute in Thoraipakkam focuses on making you employable. Trainers are working Analytics engineers and data modelling specialists, every module produces portfolio evidence rather than a completion badge, and the placement cell connects eligible candidates with hiring companies. Fee: ₹45,000 – ₹75,000. Enquire on +91 8610964691.
Career and Job Support
- Resume assistance tailored to the target role
- LinkedIn profile rewrite and recruiter outreach
- Mock interviews covering role scenarios
- Assessment and capstone walkthrough preparation
- Placement assistance with 200+ hiring partners
- Typical salary band after completion: ₹8 – 20 LPA
Frequently Asked Questions
What does the dbt Analytics Engineering course cover?
The course follows the dbt Analytics Engineering Certification exam: 65 questions in two hours, scored against modelling, testing, documentation, Jinja, macros, incremental strategies, snapshots, exposures, environments and jobs. Our eight modules mirror that structure and go further into the project work, because a certification candidate who has only read the documentation consistently fails the questions that ask which approach is cheaper or which test would have caught a bad row.
How is this different from the Data Engineering course?
The data engineering course covers the whole path: extraction, transformation, loading, orchestration and reliability across warehouses, lakes and streaming. This course is the transformation layer in depth. It is about how you structure a dbt project, how you test a model, when an incremental strategy is safe, and how you deploy through dbt Cloud environments. You need SQL for both, but only this one examines the dbt graph, the manifest and the Semantic Layer.
Do I need dbt Cloud, or can I use dbt Core?
The exam questions cover both, and the course teaches dbt Core first because that is where the modelling happens, then moves to dbt Cloud for environments, deployment jobs and the Semantic Layer. dbt Cloud has a free developer tier that is enough for the deployment modules. If your employer has no dbt Cloud account, the project can be run entirely in dbt Core with a local profile and a git repository.
How much SQL do I need before starting?
Enough to write a join, a group by and a window function without looking them up, and enough to explain where a number in a report came from. The course assumes that and does not re-teach query syntax. dbt is a tool that organises SQL rather than replaces it, so candidates who are still writing their first joins tend to get stuck on the tool instead of the modelling.
What does the exam look like and what score do I need?
It is an online proctored assessment of 65 questions in two hours, with single-answer and multi-select questions where the multi-select items are where marks are usually lost. The published passing score is 65 percent. dbt Labs recommends SQL proficiency and at least six months of hands-on dbt work, so treat the practice project in the course as the place to earn that six months in weeks rather than months.
What is the duration and fee?
Twelve weeks, three sessions a week of two hours each, totalling 72 hours, with the project built in class so that every module lands as working code. Fees run from Rs 45,000 to Rs 75,000 depending on batch and mode, with classroom, live online and hybrid options and placement support through 200+ hiring partners. A warehouse sandbox is provided, and dbt Cloud has a free tier for the deployment work.
What certificate do I receive?
A SkilBrill Course Completion Certificate for the full 72 hours of the programme, listing the modules completed and the dbt project you deployed. The dbt Analytics Engineering Certification is issued by dbt Labs after you pass their proctored assessment. We prepare you for that exam and mark your project work; we do not issue the vendor credential.