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Are you interested in becoming a dataarchitect? A dataarchitect, in turn, understands the business requirements, examines the current data structures, and develops a design for building an integrated framework of easily accessible, safe data aligned with business strategy.
This suggests that today, there are many companies that face the need to make their data easily accessible, cleaned up, and regularly updated. Hiring a well-skilled dataarchitect can be very helpful for that purpose. What is a dataarchitect? Let’s discuss and compare them to avoid misconceptions.
BigDataData engineers must focus on managing data lakes, processing large amounts of bigdata, and creating extensive data integration pipelines. These tasks require them to work with bigdatatools like the Hadoop ecosystem and related tools like PySpark , Spark, and Hive.
Using SQL queries, they design, code, test, and aggregate the results to generate insights. BigData Engineer/DataArchitect With the growth of BigData, the demand for DataArchitects has also increased rapidly. They are also responsible for improving the performance of data pipelines.
As we can see, it turns out that the data engineering role requires a vast knowledge of different bigdatatools and technologies. The data engineering role requires professionals who can build various data pipelines to enable data-driven models.
Steps to Become a Data Engineer One excellent point is that you don’t need to enter the industry as a data engineer. You can start as a software engineer, business intelligence analyst, dataarchitect, solutions architect, or machine learning engineer. You can also post your work on your LinkedIn profile.
This blog lists some of the most lucrative positions for aspiring data analysts. Among the highest-paying roles in this field are DataArchitects, Data Scientists, Database Administrators, and Data Engineers. Those who become Database Administrators can anticipate making between $80,000-1,40,000.
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