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About this interview
A technical interview on Data Ingestion and Pipeline Fundamentals, pitched at the easy level. A voice AI interviewer leads the conversation, adapts its questions to your answers, keeps you on topic, and afterward gives you honest, specific feedback on where you were strong and where to improve. Expect roughly 30 minutes.
What you'll be assessed on
Explain the difference between batch ingestion and event-driven ingestion and when to choose each
Describe how incremental loading works and why it matters for large datasets
Identify common ingestion failure modes and how to handle them (retries, dead-letter queues)
Contrast push-based vs pull-based data collection architectures
Topics covered
Pipeline FundamentalsETL vs ELTBatch IngestionPush vs PullBatch vs Event-DrivenFull LoadIncremental LoadingCDCIdempotencyAPI IngestionFailure HandlingDelivery SemanticsDeduplicationSchema Management
A few sample questions
Just examples to set expectations - the real interview has many more and adapts to your responses.
“In simple terms, what does a data ingestion pipeline do, and why is it the foundation of any data platform?
“What is API rate limiting and how would you design an ingestion job that respects rate limits while still finishing within your SLA window?
“What is late-arriving data and how does it create correctness problems in time-windowed aggregations? How would you handle it in a batch pipeline versus a streaming pipeline?