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Data Science: The Importance of Data Engineers
With the rise in the importance of data in businesses, for use in analytics, AI and Big Data processing, the role of the data engineer has only recently appeared, but it has already become an important role for many businesses.
Chris Riccomini, software engineer at WePay, defined the role of a data engineer as follows: “A data engineer’s job is to help an organization move and process data. On the movement front, we’re talking about either streaming pipelines or data pipelines. On the processing front, we’re talking about data warehouses and stream processing.”
Data engineers are strong technologists with programming skills in languages like Java, Python, and scripting tools. They have backgrounds with data integration, middleware, and extract-transform-load (ETL) projects. In the role of data engineer, they clean and reformat data so that it is readily used in business intelligence and data analytics software and by data scientists for analysis and modeling. Data engineers aggregate, clean and package data.
Demand for Data Engineers is up. Dice reports that job postings for Data Engineers is increasing 50 percent annually.
Richa Dhanda is the vice president of product marketing at Talend, wrote for Datanami that “Data engineers have become valuable resources that can harness the value of data for business objectives, which ultimately plays a strategic role in a complex landscape that is essential to the entire organization. Understanding and navigating data needs has the ability to transform data and empower data engineers to propel an organization into a thriving data-first company. As a result, organizations can stay competitive and innovative, ultimately giving C-suite execs one less thing to worry about.”
