Reaching 20k+ readers on Medium and over 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.
Can Your Data Pipelines Be Dangerous?
Extract. Transform. Read.A newsletter from Pipeline: Your Data Engineering ResourceHi past, present or future data professional! Data engineering can be dangerous; ok—not, like, physically, but by building and maintaining data infrastructure, data engineers are given a surprising amount of access and responsibility. Every commit, table alteration and deletion must be made with care. It took 2 years, but I finally learned a shortcut to make developing SQL staging tables less risky and more efficient. Even seemingly minor mistakes like joining on the wrong key can result in losing days or months of valuable data, which can be equal to hundreds of thousands or millions of dollars in revenue visibility. Outside of code mistakes, not paying attention to logistic factors like vendor contracts and API usage can not only result in downtime, in a worst-case scenario it can lead to an all-out blackout. If the stakes sound ominous, I’d suggest examining the root of your hesitation to work more confidently and efficiently—it may even be the code itself. There is a happy medium between freely building data pipelines and using the appropriate guard rails. As long as you take your time and don’t commit code directly to the main branch then you can do data engineering safely and avoid bursting your pipelines. For those who are anti-virus minded, here are this week’s links as plain text:
P.S. Want to learn how to go from code to automated pipeline? Take advantage of my 100% free email course: Deploy Google Cloud Functions In 5 Days. Thanks for ingesting, -Zach |
Extract. Transform. Read.
Reaching 20k+ readers on Medium and over 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.
Hi fellow data professional! It’s baseball season in the U.S., a game defined by the "on-deck" line up. Before a player takes a big swing at the plate, they are already there, weighted bat in hand, timing the pitcher (who has to move a bit faster now thanks to the pitch clock), fully prepared for their moment. They don’t start looking for their helmet only after the umpire calls them up. In your early career perhaps you're considering "taking a big swing" by applying for that dream role at a...
Hi fellow data professional! In undergrad, in pursuit of a coveted TV internship, I once cold messaged an alum of my school using an email I found on his acting reel. When we finally got on the phone it wasn’t the warm handshake connection I was seeking; he spent time grilling me on my intentions and skills. After I hung up I thought “what a jerk.” In my yet-to-be-developed mind I thought as long as I went to the effort of getting someone on the phone they’d reward that initiative with a job,...
Hi fellow data professional! This week I’ve gotten back into something I haven’t even attempted since my college intern days: Meal prepping. Prep is a priority for me since I’m watching my son (and our pets) solo while my wife is away for work. And, I hate to say it but, I somewhat agree with Sam Altman’s controversial quote about not understanding how people parented before widespread AI adoption; when used properly, AI-generated “parental assets” like meal plans, budgets and workout...