Lambda is serverless compute for event-driven, short-lived tasks. Roles: (1) Orchestration: Trigger Glue, EMR, or Step Functions when files land (S3), events arrive (Kinesis), or schedules fire. (2) Light transforms: JSON→Parquet, small aggregations, API calls. (3) Alerts:...
Red Flag: Suggesting Lambda for 'all ETL'—ignores timeout and memory limits. Pro-Move: Describing Lambda as trigger/orchestrator for Glue/EMR—shows correct service boundaries.
This medium-level Cloud/Tools question appears frequently in data engineering interviews at companies like EY, Incedo, Tech Mahindra. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (spark) 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.
Lambda is serverless compute for event-driven, short-lived tasks. Roles: (1) Orchestration: Trigger Glue, EMR, or Step Functions when files land (S3), events arrive (Kinesis), or schedules fire. (2) Light transforms: JSON→Parquet, small aggregations, API calls. (3) Alerts: Validate data, send Slack/PagerDuty on anomalies. Why: No server management; scale to thousands of concurrent invocations; pay per request and duration. Limitations: 15-min timeout, 10GB memory, 6MB payload (sync). Not for heavy Spark or large data—use Glue/EMR. Scalability: Lambda scales automatically; cold starts add latency (mitigate with provisioned concurrency). Cost: Very cheap for sporadic, short jobs; can spike with high event volume. Trade-off: Use Lambda for glue logic and triggers; keep heavy processing in dedicated compute.
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Analyze My Answer — FreeAccording to DataEngPrep.tech, this is one of the most frequently asked Cloud/Tools interview questions, reported at 3 companies. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.