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Describe the role of a workflow orchestrator like Airflow in a data pipeline.

Spark/Big Dataeasy0.3 min readPremium
Frequency
Low
Asked at 1 company
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Swiggy
Key Concepts Tested
airflow
Expert AnswerPremium
66 wordsInterview-ready
**Why orchestrator matters**: Pipelines are multi-step; dependencies, retries, monitoring = orchestrator's job. **Role**: Schedules (cron, triggers); manages dependencies (task order); retries on failure; monitors; ensures idempotent, reliable runs. Central place for pipeline logic. **Scalability trade-offs**: Orchestrator can bottleneck; use Celery for parallelism. **Cost implications**: Failed tasks without retry = manual intervention = cost....
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