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![]() How would you optimize a database query that’s running slowly?Īnswer: I would start by analyzing the query plan to identify any performance bottlenecks. I would also implement redundancy and fault tolerance mechanisms such as checkpointing and data replication to ensure high availability.Ģ. Then, I would use distributed computing technologies like Apache Spark or Hadoop to handle large volumes of data. How would you design a scalable and fault-tolerant data pipeline?Īnswer: I would start by breaking the pipeline into smaller components, such as ingestion, transformation, and storage. 30 Data Engineer Interview Questions with Answersġ. We present here a curated list of the top 30 data engineer interview questions with answers that will help you in preparing for data engineering based interviews. You should also be familiar with data engineering concepts and tools like ETL, data streaming, distributed systems, and cloud technologies. To crack data engineer interviews, you should have a strong understanding of databases, storage systems, pipelines, and computer science fundamentals. Data engineers are also involved in data modelling and database design, as well as managing the scalability and performance of data systems. They work with large datasets, often in real-time, and use tools like Hadoop, Spark, and SQL to create data pipelines and ETL processes. A data engineer is responsible for designing, building, and maintaining the infrastructure that supports data storage, processing, and analysis.
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