How Data Engineers Can Take Advantage of ‘Slow Weeks’
How you can provide value to your organization and refine competitive skill sets even when you don’t have much to do.
Prior to working as a data engineer I thought tech jobs mirrored HBO’s Silicon Valley — constant coding, frustration and excitement that kept you occupied all day and even into the night. However, at least in my experience, maintaining a consistent work load is not always possible, especially when the majority of your job is to deliver on ad hoc requests to internal (or external) customers. Despite what you may have imagined while in school or transitioning from a similar business intelligence role, data engineering work can be slow, sometimes for days or even a week or two. For remote workers like me it can be easy to feel disengaged during the slow times of the year. If you don’t have a meeting and don’t have a lot of projects you’re actively developing, it can feel like you’re waiting on the data engineering bench for some high-octane Python or SQL-based action.
Why Data Engineering Can Be Slow
The primary purpose of any data-oriented role is to provide value for stakeholders and decision makers within an organization. If those individuals or teams don’t require any kind of update to an…
