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They use technologies like Storm or Spark, HDFS, MapReduce, Query Tools like Pig, Hive, and Impala, and NoSQL Databases like MongoDB, Cassandra, and HBase. They also make use of ETLtools, messaging systems like Kafka, and BigDataTool kits such as SparkML and Mahout.
Azure Services You must be well-versed in a variety of Azure services, including Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Analysis Services, Azure Stream Analytics, and Azure Data Lake Storage, in order to succeed as an Azure Data Engineer.
Data is moved from databases and other systems into a single hub, such as a data warehouse, using ETL (extract, transform, and load) techniques. Learn about popular ETLtools such as Xplenty, Stitch, Alooma, and others. To store various types of data, various methods are used.
To ascertain and address data requirements, they engage with business stakeholders. In order to satisfy company demands, they are also in charge of administering, overseeing, and guaranteeing datasecurity and privacy. Programming languages like Python, Java, or Scala require a solid understanding of data engineers.
ETL (extract, transform, and load) techniques move data from databases and other systems into a single hub, such as a data warehouse. Get familiar with popular ETLtools like Xplenty, Stitch, Alooma, etc. Different methods are used to store different types of data.
Top 100+ Data Engineer Interview Questions and Answers The following sections consist of the top 100+ data engineer interview questions divided based on bigdata fundamentals, bigdatatools/technologies, and bigdata cloud computing platforms.
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