Adela began the interview by saying that she was a long-time back-end developer and made the switch to working with data a few years ago. During this transition, she realized the importance of accuracy, consistency, and quality of data. She commented that we are very used to seeing emergencies caused by a software product failure in production, but we pay very little attention when the product seems to work well but the data may be corrupted.
She went on to point out that code without testing is now unthinkable, since code of this type is considered legacy and lacks quality. However, in the world of data, it is common to see data without any proof that guarantees its consistency. Adela believes that the world of data is one step behind the world of software engineering, where no one questions the value of having tests that guarantee quality. Despite everything she believes that little by little the world of data is beginning to advance in the direction of quality — proof of this is that in more and more practices, frameworks and tools for testing data are becoming popular.
An important aspect that Adela mentioned is that the tests must be automated and run in a short time so that they can offer accurate and timely information. In this way, the product teams will be able to recognize whether the data is valid or not. She believes that all of this is part of the path to Agility that the world of data is beginning to travel. She pointed out that when automated tests report that everything is fine, this frees up developers’ time and concentration so that they can focus on other tasks that add value.
In her opinion, developers who work with data must know technical aspects but also the domain to which the data belongs. Knowing the domain within which the software product will operate enables the data engineer to be able to make better abstractions and include only the necessary data.
Adela considers that one of the main contributions of Agile for data engineers has been to get them to consider developing products in small increments that add value early — translated for the world of data, this above implies developing the database incrementally and always taking care of its quality through automated tests.
To close the interview, Adela shared her vision of where data engineering will evolve in the next five years. In her opinion, data engineers in the future will have already assumed the importance of data quality and their practices and tools will have reached a degree of maturity, similar to that already found in software engineering.
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