Data Engineer Technical Interview Questions

Review this list of 5 technical data engineer interview questions and answers verified by hiring managers and candidates.
  • Amazon logoAsked at Amazon 

    "OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) are two types of data processing systems, each designed for specific purposes in the context of database and data warehouse environments. OLTP (Online Transaction Processing):Purpose: OLTP systems are designed to manage and handle high volumes of transactions, such as inserting, updating, and deleting data. These systems are typically used in day-to-day business operations. Characteristics: Handles small, si"

    Nikunj V. - "OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) are two types of data processing systems, each designed for specific purposes in the context of database and data warehouse environments. OLTP (Online Transaction Processing):Purpose: OLTP systems are designed to manage and handle high volumes of transactions, such as inserting, updating, and deleting data. These systems are typically used in day-to-day business operations. Characteristics: Handles small, si"See full answer

    Data Engineer
    Technical
    +1 more
  • "i said there is hashed, clustered, non-clustered"

    Erjan G. - "i said there is hashed, clustered, non-clustered"See full answer

    Data Engineer
    Technical
  • "i did not know ,but the answer is parquet is column-oriented, avro is row-oriented"

    Erjan G. - "i did not know ,but the answer is parquet is column-oriented, avro is row-oriented"See full answer

    Data Engineer
    Technical
  • "i failed to answer, did not know"

    Erjan G. - "i failed to answer, did not know"See full answer

    Data Engineer
    Technical
  • "I have worked with tools such as Hadoop, Oracle, DBeaver, and Databricks. I have used these tools at work when dealing with large datasets, data cleaning, data security, and creating models"

    Aneesh D. - "I have worked with tools such as Hadoop, Oracle, DBeaver, and Databricks. I have used these tools at work when dealing with large datasets, data cleaning, data security, and creating models"See full answer

    Data Engineer
    Technical
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