Analytics Engineering Case Study

This project contains the end-to-end data pipeline for the Analytics Engineer task - to measure driver engagement. It covers everything from initial Snowflake setup to final reporting models.

Where to start

• Appendix AE.pdf: Start here for a detailed technical overview of the logic, data quality decisions, and architectural choices.

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🏗 Project Structure

• setup.sql: The entry point for the project. Run this first to set up the Snowflake environment (databases, schemas, and stages).
• models/: Contains the core transformation logic divided into three layers:
  • /staging: Initial cleaning and data quality flagging (casting types, handling "ghost drivers").
  • /marts: Final dimensional models (Facts and Dimensions) ready for BI tools.
  • /analyses: Ad-hoc SQL queries and the Exploratory Data Analysis (EDA) notebook used to uncover trends.

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🚀 How to use this repository

1. Run the setup.sql script in your Snowflake console.
2. Follow the loading order described in the Appendix: Drivers -> Bookings -> Offers.
3. The final aggregated metrics can be found in the agg_driver_activity.sql model within the marts folder.