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Updated weekly · Last refresh Sep 12

Top 50 data streams Interview Questions

The most frequently asked data streams questions across all roles and companies, ranked by real interview frequency. Updated daily.

50questions
~7htotal time
47companies covered
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1
System DesignStart here. 22 questions · ~183 min
Real-Time Anomaly Detection at ScaleHard

Design a streaming ML pipeline that detects anomalies across spans, metrics, and logs at million-event-per-second scale.

pipeline designdistributed systemsanomaly detectionCiscoBMC Software
Asynchronous Streaming Pipeline ArchitectureHard
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Design a resilient Kafka and Spark pipeline with durable ingestion, stream processing, replay, observability, and optional ML inference.

kafkadistributed systemsdata ingestionApple
DWH for Employee Hours and HeadcountHard

Design a data warehouse for employee hours, headcount, and hiring and attrition metrics by department and building.

enterprise architecturedata ingestiondata streamsAmazon Web Services
Real-Time Inventory at ScaleHard

Design a scalable inventory tracking system with real-time updates, accurate state, anomaly detection, and resilient serving.

distributed systemsscalabilityanomaly detectionQXO
Batch Clickstream ArchitectureHard

Design a resilient global batch clickstream pipeline that produces and emails weekly subscriber reports.

data ingestiondata streamsdata collectionApple
Checkpointing in Data StreamingHard

Explain checkpointing in data streaming pipelines, including state recovery, processing guarantees, and failure tradeoffs.

distributed systemsdata streamsfailure modesAccenture Federal Services
Batch vs Streaming HandlingHard

Explain how data pipelines process, count, reconcile, and monitor batch versus streaming records.

distributed systemsdata ingestiondata streamsAccenture Federal Services
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2
Pipelines7 questions · ~58 min
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3
Coding13 questions · ~108 min
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4
Technical Fundamentals4 questions · ~33 min
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5
More topics4 questions · ~33 min
Blocking a Risky API IntegrationMedium

Tests ownership and influence in evaluating third-party API risk under delivery pressure, especially when approval affects sensitive data access.

APIsthird-party riskdata streamsMicro1
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