1. Naming Conventions
- Consistent naming for pipelines, mappings, tasks, and parameters.
- Names reflect business purpose (e.g., sales_order_staging_load).
- Avoid cryptic or developer-specific abbreviations.
2. Modularity & Reusability
- Reusable components or templates for common patterns (CDC, SCD Type 2, lookups).
- Clear separation of extract, stage, transform, load phases.
- Avoid copying pipelines—parameterize instead.
3. Documentation & Clarity
- High-level purpose documented for every pipeline.
- Inline comments for complex expressions or business rules.
- Architectural and design artifacts stored in version control.
4. Configuration Management
- Externalize connection strings, paths, environment settings.
- Follow consistent folder structures across environments.
- Keep all code and configuration under version control.
5. Testing & Validation Practices
- Regression scenarios available for critical pipelines.
- Data validation rules documented per domain.
- Unit tests or component tests where possible (especially in SQL/Spark transformations).
Maintainability issues multiply over time. Automated checks surface them early so teams can refactor proactively rather than waiting until migrations or failures force a rewrite.