Real questions from top companies · hard
Explain the CAP theorem and its relevance in distributed systems.
Explain why lineage in Spark is crucial for fault tolerance.
Given a problem statement, collaborate with your team to design the entire pipeline architecture.
Handle schema evolution in production.
Handling pipeline bugs
Handling pipeline overload situations
Have you worked with Oozie? If yes, can you explain what it is and how it's used in data pipelines?
High-level ETL Pipeline Design using tools like Kafka or Flink for new use cases?
How do you ensure data quality and consistency in your pipelines?
How do you ensure data quality in a big data pipeline, and what strategies do you use for data validation?
How do you ensure data quality in an automated pipeline?
How do you ensure fault tolerance during large-scale data migrations?
How do you ensure your pipelines are serving reliable and correct data?
How do you handle production deployment?
How do you handle schema evolution in a system with multiple data sources and consumers?
How do you monitor and troubleshoot data pipeline failures in Data Fusion?
How do you optimize data ingestion?
How do you pass global variables between pipelines?
How do you use dependency tracing to identify root causes in pipeline failures?
How does HDFS handle fault tolerance?
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