In this post we explore building reliable and scalable data pipelines with Python. We'll cover project structure, orchestration, incremental loads, monitoring, and testing.
Architecture
Start with clear separation of ingestion, transformation and serving layers...
Tools & Tips
- Use modular code and small, testable steps.
- Prefer idempotent transforms and checkpointing.
- Monitor job durations and data quality metrics.