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Explain your cloud-based data pipeline on AWS

Cloud/Toolshard0.3 min read

Reviewed by Aditya Kumar · Last reviewed 2026-03-24

Situation: Built data platform for analytics and ML. Architecture: S3 landing (API Gateway + Lambda, Kinesis Firehose) → Glue crawlers → Glue ETL (Parquet, curated) → Redshift/Athena. Streaming: Kinesis → Lambda/Kinesis Analytics → S3. Step Functions for multi-step. Medallion...

🤖 Analyze Your Answer
Frequency
Low
Asked at 1 company
Category
179
questions in Cloud/Tools
Difficulty Split
104E|27M|48H
in this category
Total Bank
1,863
across 7 categories
Part of the ETL Pipeline Design & Orchestration Interview Preparation Hub
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Reported in Interview Loops AtClick to view company-specific questions
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Key Concepts Tested
etlpartition
Expert Answer
57 words

Situation: Built data platform for analytics and ML. Architecture: S3 landing (API Gateway + Lambda, Kinesis Firehose) → Glue crawlers → Glue ETL (Parquet, curated) → Redshift/Athena. Streaming: Kinesis → Lambda/Kinesis Analytics → S3. Step Functions for multi-step. Medallion (raw/silver/gold). Result: Single lake; Glue Catalog; partition by date; encrypted; Terraform. Best practice: Monitor CloudWatch; IaC for infra.

⚡
Pro Tip

Red Flag: Describing architecture without mentioning failure handling. Pro-Move: 'Medallion architecture; Step Functions with Catch for failures; we replay from S3 on bug—here's our diagram.'

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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.

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