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LogoutAs a Big Data Engineer, you will collect data from various sources, transform it into useful information, and load it into other data storage systems.
Talend, IBM Datastage, Pentaho, and Informatica are some of the tools used.
Some other tools are as follows:
Operating System: Knowledge of operating systems is the fourth talent you need.
The foundation for running Big Data tools is operating tools. As a result, a thorough knowledge of Unix, Linux, Windows, and Solaris is required.
Hadoop tools and frameworks: Prior familiarity with Hadoop-based analytics is required. Given that Hadoop is one of the most widely used Big Data engineering tools, you should be familiar with Apache Hadoop-based technologies such as HDFS, MapReduce, Apache Pig, Hive, and Apache HBase.
Apache Spark: Working with real-time processing frameworks like Apache Spark is the sixth talent you need. Because you will be dealing with massive amounts of data as a Big Data Engineer, you will need an analytics engine like Spark to handle batch and real-time processing.
Spark can process live streaming data from various sources, including Twitter, Instagram, and Facebook.
Data mining and modeling: To meet the final skill level, you must experience data mining, data wrangling, and data modeling approaches.
Preprocessing and cleaning data using various methods, finding undiscovered trends and patterns, and preparing it for analysis are all phases in data mining and data wrangling.