A: They asked me to walk through a real-world Spark use case I’d implemented—building a streaming ETL for clickstream data—detailing how I managed stateful windowed aggregations, tuned `spark.sql.shuffle.partitions`, and fixed data skew with a custom partitioner.
What are your experiences in data engineering?
"They asked me to design an end-to-end data pipeline that supports both batch and real-time processing using tools like Kafka, Spark, and a cloud platform like AWS or Azure. They were particularly interested in how I’d handle schema evolution and ensure data quality at each stage."
What is your background in Python, AWS, and Glue?
Implement iterator which take 3 iterator as Input and sort it out.
Explain the differences between a analytics modeling and transactional modeling
Python list of lists containing nodes with parent , child relationship and find the node that has max connections.
More about your way of thinking with experience
What is polymorphism?
Python 1D and 2D Arrays, behavioral questions.
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