Top data engineering writer on Medium & Senior Data Engineer in media; I use my skills as a former journalist to demystify data science/programming concepts so beginners to professionals can target, land and excel in data-driven roles.
[ETR #19] 1 Question New Data Engineers Can't Ask
Extract. Transform. Read.A newsletter from Pipeline Hi past, present or future data professional! I recently participated in a technical design meeting that was derailed by a single, fundamental question. “Why?” Despite the fact that I worked with the particular data source we were discussing for nearly two years, I fell into the common trap of going “on autopilot” and failing to question the initial need for the data. At this point, you would think asking “why” of years’ worth of work would be offensive. Instead of myself or other team members getting defensive, it led to a productive conversation about not just refining our approach to ingestion, but also inspired talk of how we can manage stakeholder expectations and softly encourage them to “do more with less.” Fortunately, you don’t need to derail a meeting to leverage what I call a productive why. Asking occasional, tactful “whys” can position you as a critical thinker and thought leader (or at least an enthusiastic thought contributor) within your org. When appropriate, consider asking…
I realize you may not be in a professional role; nonetheless, I’ve found a lot of value can result from occasionally asking “why” even when you’re simply writing code. For instance, I was a habitual user of Pandas’ .append() method. Unfortunately, to my disappointment, Pandas 2.0 deprecated .append() in the past year. I easily could have panicked and said “Iterating and appending key values to an empty data frame is how I’ve always converted JSON to a data frame. What am I going to do?” But being forced to adapt to the change made me think about what prompted that habit initially. To learn what that motivation was plus how a simple "why" nearly left me tongue-tied in an interview, read the latest on Pipeline. And so you don’t have to question where those hyperlinks go, here they are as plain text.
Questions? zach@pipelinetode.com Thanks for ingesting, -Zach Quinn |
Pipeline To DE
Top data engineering writer on Medium & Senior Data Engineer in media; I use my skills as a former journalist to demystify data science/programming concepts so beginners to professionals can target, land and excel in data-driven roles.
Extract. Transform. Read. A Newsletter From Pipeline Hi past, present or future data professional! Since today marks Thanksgiving in the US, I hope this reaches you before your eyes glaze over from the tryptophan-induced turkey coma we all inevitably slip into. While today is a day of gratitude, from a data engineering perspective, I’d like to focus, instead, on the under-the-radar tasks that can make a difference at this time of year—even if they don’t gain you any recognition at work. The...
Extract. Transform. Read. A newsletter from Pipeline Hi past, present or future data professional! It’s never good when you wake up to this from a coworker: 💀 The skull wasn’t because the sender felt like they would suffer any kind of dramatic fate. Instead, they were prepared to administer near-fatal justice to the junior engineer who made several unnecessary overnight commits straight to our org’s main branch. The thing is, for a first-time violation, I can understand why testing is an...
Extract. Transform. Read. A newsletter from Pipeline Hi past, present or future data professional! It’s been a busy fall; I currently have 14 tasks in various states of development. Right now my JIRA board looks like I just won bingo—twice. Unfortunately when you climb the tech ladder things only get busier which means you’re going to burn out unless you take steps toward proactivity. For me this means learning which tasks I don’t need to (and really shouldn’t) do manually. And before you...