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! It’s the most wonderful time of the year… performance reviews. Depending on your outlook on your job/org, that “wonderful” could be sarcastic. However, if you’ve landed on your manager’s nice list, this can be the time to recap your achievements to maintain credibility and work toward the next rung on the corporate ladder. If you’re on a small team serving demanding stakeholders it’s possible...
Extract. Transform. Read. A newsletter from Pipeline. Hi past, present or future data professional! This holiday season will be a little less bright thanks to my lack of personal GitHub commits. Like you, I began 2024 full of ideas and motivation that, let’s be honest, was depleted by the end of Q1 when I was cranking out enough code at work that would please even notorious code volume stickler Elon Musk. Despite my lacking output, I managed to hunker down to create useful “bespoke” (a.k.a....
Extract. Transform. Read. A newsletter from Pipeline. Hi past, present or future data professional! When I worked at Disney there was one line (aside from “Have a Magical Day”) that was borderline beaten into us: “We are all custodial employees.” The line meant, of course, to keep areas under your purview neat and presentable (“show ready” in Disney-speak). Using the same logic, I’d like to emphasize that while the various data roles (data analyst, data scientist, data engineer, etc.) have...