Data / Cohort
Pipeline Engineering with SQL + dbt
Versioned transformations, tests, and observability hooks for analytics engineers.
Overview
You build incremental models, document exposures, and wire basic data quality tests. Labs mirror evening batch windows common to Vietnam-based analytics teams serving global stakeholders.
What is included
- dbt project scaffold with Flux Blaze naming conventions
- Incremental model lab with merge strategies
- Data tests tied to business assertions
- Lineage diagrams exported for stakeholder decks
- Observability hooks using open-source alerts
- Pair rotation with teaching assistants
- Portfolio review with a career coach
Outcomes you can show
- Maintain a dbt repo with at least eight documented models.
- Automate two data tests that map to finance-approved metrics.
- Present lineage and freshness guarantees to a mock steering group.
Experience notes
“Incremental lab mirrored our midnight loads—Hien’s test suggestions caught a timezone assumption I had carried from Excel.”
“Lineage export impressed my manager; still wish we had one more week on snapshots.”
FAQ
Prerequisites?
You should graduate SQL Foundations or demonstrate equivalent joins and CTE fluency via a skills check.
Cloud costs?
Sandbox warehouses include capped credits; overages are learner responsibility if you fork projects.
Limitations?
We do not cover proprietary ETL appliances; focus stays on SQL-first tooling.