A hands-on project that builds a modern ELT pipeline and dashboard entirely in code — using Python, BigQuery, and Streamlit.
It transforms raw event data from Google’s public GA4 sample dataset into analytics-ready tables and KPIs.
Analytics Engineering Concepts
- Build a warehouse-native ELT pipeline (staging → core → marts)
- Design dimensional models with clean joins and incremental logic
- Govern transformations using SQL stored as code (version-controlled)
- Use Python orchestration for parameterized BigQuery jobs
Technical Skills
| Area | Tools / Skills |
|---|---|
| Data Warehouse | Google BigQuery, SQL (CTE, aggregation, window functions) |
| Orchestration | Python (google-cloud-bigquery, environment configs) |
| Modeling Layers | Staging, Core, Mart tables |
| Visualization | Streamlit (interactive KPI dashboard) |
| DataOps | Virtual environments, Git version control, reproducible pipeline |