Reviewed by Aditya Kumar · Last reviewed 2026-03-24
**Architectural cost logic**: At scale, 10–20% savings = millions. Prioritize by spend: compute (Glue/EMR/Lambda), storage (S3), and data transfer. **Compute**: Right-size—Glue bills by DPU-minute (10 DPU minimum); profile jobs and start at 10, scale only if I/O-bound. Use Spot...
This medium-level Cloud/Tools question appears frequently in data engineering interviews at companies like Wipro. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (partition) will help you answer variations of this question confidently.
Break this problem into components. Identify the core trade-offs involved, then walk the interviewer through your reasoning step by step. Demonstrate awareness of edge cases and production considerations - this is what separates good answers from great ones.
Architectural cost logic: At scale, 10–20% savings = millions. Prioritize by spend: compute (Glue/EMR/Lambda), storage (S3), and data transfer. Compute: Right-size—Glue bills by DPU-minute (10 DPU minimum); profile jobs and start at 10, scale only if I/O-bound. Use Spot for Glue/EMR where fault-tolerance exists (checkpoints, idempotent writes); we achieved 40% EMR savings. Reserved Instances/Savings Plans for steady-state (e.g., always-on clusters). Storage: S3 Intelligent-Tiering for unknown access patterns—no retrieval fees vs. Glacier. Compress data (Parquet/ORC)—3–5× reduction cuts scan costs in Athena. S3 lifecycle to Glacier for cold data; delete incomplete multipart uploads. Query cost: Athena charges $5/TB scanned—partitioning + columnar formats + partition projection can cut scans by 80%. Governance: Cost Explorer, Budgets, tags for chargeback. At 100 TB storage + 50 TB monthly scans, savings from compression and tiering can exceed $5K/month.
Pro-Move: 'We run a weekly cost anomaly report and tag all resources with project/env—when Glue costs spiked 2×, we traced it to a new job running at 64 DPUs unnecessarily.' Red Flag: Generic advice without numbers—senior engineers quantify impact.
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According to DataEngPrep.tech, this is one of the most frequently asked Cloud/Tools interview questions, reported at 1 company. DataEngPrep.tech maintains an editor-reviewed database of 1,863 data engineering interview questions across 7 categories.