Your question is Robust Distributed Error Handling. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
How do you implement robust error handling in a distributed data pipeline?
Explain a practical design using technologies such as Apache Kafka, Apache Spark Structured Streaming, object storage, and a warehouse. Address transient versus permanent failures, retry policies, dead-letter queues, poison messages, checkpointing, idempotent writes, schema violations, partial failures, replay and backfill procedures, alerting, and data quality monitoring. Describe how you would preserve ordering where required, avoid duplicate records during recovery, and make failures diagnosable without silently dropping data.