**Section 1 — The Context (The 'Why')**
End-to-end data pipelines must reconcile batch (S3, databases) and streaming (Kafka, Kinesis) sources into a unified lakehouse or warehouse. The primary challenge is orchestrating ingestion, transformation, and serving while handling schema evolution, late-arriving data, and maintaining lineage for compliance....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like Apple. The answer also includes follow-up discussion points that interviewers commonly explore.
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