**Retry:** Exponential backoff + jitter. Libraries: tenacity (Python), resilience4j (Java). Max 3–5 retries; cap backoff. **When:** Transient only (5xx, timeouts); not 4xx. **Workflows (Airflow, Step Functions):** retry_delay, retries on task; DLQ for permanent failures....
This easy-level General/Other question appears frequently in data engineering interviews at companies like TCS. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (airflow, python) will help you answer variations of this question confidently.
Start by clearly defining the core concept being asked about. Interviewers want to see that you understand the fundamentals before diving into implementation details. Structure your answer with a definition, then explain the practical application with a concise example.
Retry: Exponential backoff + jitter. Libraries: tenacity (Python), resilience4j (Java). Max 3–5 retries; cap backoff. When: Transient only (5xx, timeouts); not 4xx. Workflows (Airflow, Step Functions): retry_delay, retries on task; DLQ for permanent failures. Critical: Idempotent ops; idempotency keys for APIs. Cost: Retries increase load—tune max; log for observability. Scalability: DLQ prevents backlog blocking.
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Analyze My Answer — FreeAccording to DataEngPrep.tech, this is one of the most frequently asked General/Other interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.