Should Data Engineers care only about technical knowledge???

Working at the intersection of business and technical teams brings perks and growth opportunities for any data engineer.

With this great opportunity comes the responsibility to be a bilingual (if not multilingual) person who can switch the language based on the stakeholder while interacting with them.

A data engineer typically interacts with their immediate customers like data analysts, data scientists or machine learning engineers for their different data needs.

It is important that we as data engineers not only focus on learning about technical stuff like new features or some bug in spark, but also spend time to understand about the actual business of our clients.

Of course, considering people think data engineers are a different version of software engineers (opinionated statement I know), we are expected to be techies!

Knowing how the business operates in the context of data will be handy when there is one odd data point, coming from that Kafka source or some third-party data source, isn’t making sense for the business stakeholder and they come back to you for the deep dive around that.!

Handling the quality of the data going into the ML model or that pretty dashboard is undoubtedly important, but knowing your data and understanding the use of the data with actual domain insights do wonders when it comes to gauging the real effectiveness of the data engineer role.

If you are or were a data engineer, how do you make sure this balance is in place?

Do you weigh contextual knowledge and technical knowledge equally?

Do let me know in the comments below! :)

p.s.: This piece was originally posted on LinkedIn here.

Do connect with and/or follow me if you resonated with this. :)