Reviewed by Aditya Kumar · Last reviewed 2026-03-24
**Why S3 Cleanup:** Storage costs grow; lifecycle policies handle automated deletion but custom logic (retention by prefix, exclude patterns) needs scripting. **Implementation:** list_objects_v2 with paginator (handles 1000+ keys). Filter by LastModified. delete_objects in...
This easy-level Python/Coding question appears frequently in data engineering interviews at companies like Moonfare. While less common, it tests deeper understanding that distinguishes strong candidates.
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.
Why S3 Cleanup: Storage costs grow; lifecycle policies handle automated deletion but custom logic (retention by prefix, exclude patterns) needs scripting.
Implementation: list_objects_v2 with paginator (handles 1000+ keys). Filter by LastModified. delete_objects in batches of 1000 (max per request)—reduces API calls.
Cost/Safety: Each LIST = $0.005 per 1000; DELETE is free. Add dry-run mode. Use versioning + MFA delete for production. Consider S3 Lifecycle (Transition/Expiration) instead of scripts for standard retention—cheaper and automatic.
paginator = s3.get_paginator('list_objects_v2')
for page in paginator.paginate(Bucket=b, Prefix=p):
keys = [o['Key'] for o in page.get('Contents',[]) if o['LastModified'] < cutoff]
if keys:
s3.delete_objects(Bucket=b, Delete={'Objects':[{'Key':k} for k in keys]})
Red Flag: Deleting without dry-run or backup. Pro-Move: 'We use S3 Lifecycle for standard retention; script only for custom logic (exclude prod prefix, tiered retention).'
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According to DataEngPrep.tech, this is one of the most frequently asked Python/Coding interview questions, reported at 1 company. DataEngPrep.tech maintains an editor-reviewed database of 1,863 data engineering interview questions across 7 categories.