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.
Why Put Emojis In A Data Pipeline? 😎
Extract. Transform. Read.A newsletter from Pipeline: Your Data Engineering ResourceHi past, present or future data professional! I bet when you think of data engineering tools, you don’t think of smiley faces. But emojis, when used properly (and sparingly), can be a powerful way to emphasize logging messages and highlight infrastructure failures. Failing in data engineering can make you :sad_face:. Professionally, I’ve made every code mistake imaginable, with the highlight being omitting a column and needing to process a 45 TB table—twice! Even as I gain experience, I still make (but recover from) plenty of mistakes, which I document on a yearly basis. Since we’re a little more than halfway through the year, I’d encourage you to use this framework to honestly assess both your technical and interpersonal shortcomings as an aspiring data engineer. Proactively identifying areas of improvement is growth—and areas for improvement will pay more dividends than cramming in upskilling sessions. It might even make you :smiling_face: Here are this weeks un-embedded links:
P.S. – there’s a fun announcement coming in next week’s email. Thanks for ingesting, -Zach |
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.
Hi past, present or future data professional! If you’re in the U.S., Happy Thanksgiving! I’m prepping for my food coma, so I’ll make this week’s newsletter quick. Like millions of Americans, I’ll be watching NFL football (go Ravens!). The average NFL game is 3 hours. If you can skip just one of today’s games and carve out that time for professional development, here’s how I’d spend it. In the spirit of football, I’ll split the time designation into 4 quarters. Documentation pass - if you read...
Extract. Transform. Read. A newsletter from PipelineToDE Hi past, present or future data professional! In 2 weeks or so The Oxford English Dictionary will reveal its 2025 word of the year, a semi-democratic process that lends academic legitimacy to words like “rizz” (2023’s pick). If you’re currently employed or interact with white collar workers, you would think the word of the year is “headwinds.” Used in a sentence: “We’ve pivoted our AI strategy but still encountered headwinds that...
Extract. Transform. Read. A newsletter from PipelineToDE Hi past, present or future data professional! After choosing a dataset, one of the most significant decisions you must make when creating displayable work is: How am I going to build this thing? For some, you may try to “vibe code” along with an LLM doing the grunt technical work. If you choose this approach, be warned: Nearly half of all “vibe code” generated contains security vulnerabilities and that’s before you even consider its...