project · 2022-2024
ETL template for usage analytics
Refactored a fragmented set of analytics pipelines into a reusable Python template with consistent ingestion, transformation, testing, and operational behaviour.
The problem
An analytics estate had grown through independently authored pipelines. Each used different conventions for configuration, retries, logging, and table handling, which made changes expensive and onboarding slow.
Approach
- Designed a small object-oriented template around explicit extract, transform, and load responsibilities.
- Moved shared connection handling, observability, validation, and retry behaviour into the framework.
- Kept project-specific business logic in clearly defined extension points.
Outcome
New pipelines started from a reliable baseline and existing pipelines became easier to review, test, and operate.