Reaching 20k+ readers on Medium and nearly 3k learners by email, I draw on my 4 years of experience as a Senior Data Engineer to demystify data science, cloud and programming concepts while sharing job hunt strategies so you can land and excel in data-driven roles. Subscribe for 500 words of actionable advice every Thursday.
[ETR #18] What Makes Data Engineers Say "No"
Extract. Transform. Read.A newsletter from Pipeline Hi past, present or future data professional! When I worked at Disney, the absolute worst thing you could say to a guest was “No.” It’s not so much that Disney guests would hear “yes” throughout their vacation; they just wouldn’t hear no. And that’s why, as a developer and individual contributor, it’s important to master what The Art of Being Indispensable At Work author Bruce Tulgan calls the “good no.” A bad no is a no said to something that could be feasibly accomplished. A good no is a no uttered in an effort to establish or reiterate priorities, like telling a stakeholder “No that dimension can’t be added to the pipeline during this sprint because it will require a new request to a separate API endpoint.” Good nos can also put requests into the context of larger team and organizational goals; for instance, saying “no” to production-izing an ML model that only generates 15 rows of data that isn’t relevant to larger initiatives is, without a doubt, a good no. It’s not just the sentiment of a denied request that can irritate a stakeholder or colleague. The word “no” just doesn’t sound good. It’s sharp. Definitive. If I can’t say “yes” to someone, I focus on fulfilling two needs that are almost as good:
Providing context: “I can’t put your query into production because I’m currently working on x initiative which impacts our team’s OKR for this quarter.” Offering an alternative: “Unfortunately, I don’t have the bandwidth to take on a backfill of your requested scope. Instead, I can backfill the data to the prior quarter so you can at least see data within the last 90 days, which is what your dashboard seems to focus on.” Even if you’re not working in a data role currently, this lesson can be applied to the bane of most students’ existence: Group projects. Putting your efforts into context can help avoid scope creep and make sure you don’t end up with a disproportionate amount of work. And so you don’t end up with too much work, here are this week’s links as plain text.
Questions? zach@pipelinetode.com Thanks for ingesting, -Zach Quinn |
Extract. Transform. Read.
Reaching 20k+ readers on Medium and nearly 3k learners by email, I draw on my 4 years of experience as a Senior Data Engineer to demystify data science, cloud and programming concepts while sharing job hunt strategies so you can land and excel in data-driven roles. Subscribe for 500 words of actionable advice every Thursday.
Extract. Transform. Read. A newsletter from Pipeline Hi past, present or future data professional! I dreaded entering the job market after my data science master's. I felt like I knew more than a data analyst but less than a professional data scientist. I've since realized my program was more effective than I thought, but it couldn't prepare me for the key areas like cloud deployments and real-world problem-solving I had to learn on the job as a data engineer. And I’ve noticed these gaps in...
Extract. Transform. Read. A newsletter from Pipeline Hi past, present or future data professional! If you live in the U.S., this week marks the end of back to school season; though, if you’re like my southern relatives, you’ve been back since July. The closest feeling most adults get to back to school (aside from the teachers), is starting a new job. While a new org, title and compensation package represents new opportunities, it’s also easy to feel like the “new kid”, which can lead to being...
Extract. Transform. Read. A newsletter from Pipeline Hi past, present or future data professional! I once participated in a remote job interview in which the interviewer was on the video call while driving... and smoking. While that instance was among the most memorable interview experiences (for the wrong reasons), I’ve had just as many interviews that have blended together and faded into the recesses of my mind. The common denominator, however, was the insistence on asking one question. The...