What are the best practices for designing a scalable data pipeline architecture? or How do you handle

Decoupling is key, but don’t over-engineer it. I’ve seen teams waste months on "perfectly" decoupled systems that added more latency than value.

For data pipeline architecture, start simple:
- Batch vs. streaming? Pick one *first*.
- Use managed services (BigQuery, Snowflake) if you can.

Monitoring? ELK stack works, but it’s heavy. Lightweight option: VictoriaMetrics.