Data engineers build data pipelines. They’re also the backbone of data infrastructure design and algorithm development. To build such a rich data infrastructure, data engineers require a mix of different programming languages, data management tools, data warehouses, and whole sets of other tools for data processing, data analytics, and AI/ML.
With a detailed focus on Python and SQL, this week's post will illustrate the tools that data engineers use to create effective, efficient data architecture.
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