Give an example of when you proposed changes to improve data reliability and quality. Did these changes end up being implemented? If not, why not?
"I believe that the work I produce is only as good as the data or evidence I have to back it up. That's why it is important as a Data Engineer to continuously ensure that the data your company collects and relies on to make strategic decisions is clean and of high quality. If not, I need to help identify the issues and possible solutions to improve the data. As I work on any project, I am continually evaluating whether there is a more efficient or effective process to accomplish the task at hand."
"Working as a Data Engineer, I am likely one of the employees most familiar with the company's data. Because of this, I have been able to quickly identify anomalies or issues with the data. However, I recognize that there are many people that work with various data across the company. Therefore, I appreciate the importance of getting input from other departments in the company. So when a data quality issue arose while working at my last position, I reached out to other groups within the company to build a cross-functional team to identify issues and develop a remediation plan. To this day, this group meets on a bi-weekly basis and has broadened its scope to proactively deal with upcoming issues or changes that may affect data reliability or quality."
Continuous improvement of the current environment is something hiring managers value. It is even more advantageous for you if these proposed changes were self-initiated and were not an assigned task, so be sure to highlight this if that is the case. This will display your ability to 'think outside the box' and the priority you place on quality of the company's work overall. If you have never had an opportunity to propose changes to improve data reliability and quality, explain why you think it's important and what you would do as a Data Engineer to ensure the data quality was always at a high level. In addition, if your proposed changes were not implemented for reasons such as lack of time or resources, go ahead and state that, but make sure you emphasize your continued commitment to finding new ways to improve data quality.
"While working in previous positions related to data, data quality and reliability were always things I considered as high priorities in my projects. While working on one particular project, I noticed there were several discrepancies and outliers in the data being stored in the company's database. After identifying several examples of this, I built a case to develop a data quality process into our department's routine. This included conducting a weekly meeting with representatives from different departments within the company to identify and troubleshoot data issues. Although this took time away from other projects, everyone felt it was well worth it, and in the long run, saved us from dealing with larger problems that would've been more costly for the company."