An explanation of data architects vs. data engineers

In this video, TechTarget editor Jamison Cush talks about the difference between data architects and data engineers.

Data architects and data engineers: What's the difference?

Considering the similar set of skills and responsibilities between data architects and data engineers, it makes sense that the two roles are often confused or conflated. While each position requires expertise in data management and IT, they're not the same.

Here, we'll discuss the main differences between data architects and data engineers.

The main differences between the two roles lie in the day-to-day tasks and responsibilities. Think of how an architect and engineer work together on a building project. An architect creates a design and the engineer tests and executes the design.

Data architects are responsible for designing the blueprint for an organization's data management framework. They define the policies and procedures to be used in collecting, organizing and accessing company information.

They also act as a bridge between business operations and IT, which requires both business and technical skills. In general, data architects must be well versed in the principles of data management, as well as their enterprise's IT environment. In addition, direct experience with data and web technologies is essential.

Data engineers, on the other hand, are data transfer and storage experts. They integrate, consolidate, cleanse and structure data for use in analytics applications.

In terms of skills and qualifications, proficiency in programming languages like C#, Python and Java is a must. And becoming a data engineer requires expertise in machine learning, ETL tools and business intelligence platforms, among other technical skill sets.

In a nutshell, the data architect is responsible for creating high-level data management practices, which the engineer then uses to build a data framework. Understanding the differences is useful not only to job seekers, but for managers looking to assemble a data management team that is both versatile and effective.

Goals of the data architect do overlap with those of the data engineer, so collaboration between them and the rest of the data management team is the main driver of effective work.

Did we miss any other differentiators? Let us know in the comments, and remember to like and subscribe for more videos on all things business tech.

Tommy Everson is an assistant editor for video content at TechTarget. He assists in content creation for TechTarget's YouTube channel and TikTok page.