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This article discusses the various tools and technologies used by data engineers to extract, transform, and load data into databases. It highlights the popularity of Python as a language for data engineering and the features of popular databases such as SQL, PostgreSQL, and MongoDB. It also mentions Apache Spark as a powerful framework for processing big data.