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.
You Can Build A Data Pipeline In <90 Min.
Extract. Transform. Read.A newsletter from Pipeline: Your Data Engineering ResourceHi past, present and future data professional! Since today is a U.S. holiday, I won’t take much of your time; the good news is that, when conducted efficiently, building a data pipeline doesn’t have to take days, weeks or months. In fact, you can build a data pipeline in as little as 90 minutes. Accelerating pipeline development depends on a thorough read of the documentation, a familiarity with your scripting language’s requests library and patience dealing with pesky data structures. If you think, during this time, engineers are heads-down, you may have watched The Social Network too many times; personally, I like a little external stimuli while coding, which is how I ended up building a full dashboard during another American pastime–a baseball game. My secret? Distilling data with clean views, which I recommend over bloated source tables for both aesthetic and performance reasons. Even optimizations like views have their limitations, leading to optimization ceilings. The best way to break through, aside from stubbornness, is a combination of incremental problem-solving and “big picture” data modeling to reassess resources and attack the problem completely. Since I don’t want you to have to work any harder today, here are the embedded links as text:
If you’re celebrating America today, happy 4th! 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.
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...
Extract. Transform. Read. A newsletter from PipelineToDE Amid layoff announcements from Meta, Amazon and even UPS, it's job aggregator Indeed that signals a different concern for entry-level data job seekers. This week a post on Blind revealed Indeed’s plan to quietly reduce junior roles. They’re not necessarily going to stop hiring or layoff juniors (though they are losing 1300 employees by end of year)—they’re just going to stop paying attention to them. Specifically, Indeed will no longer...
Extract. Transform. Read. A newsletter from PipelineToDE Hi past, present or future data professional! I want to share the single most important realization I had back in the summer of 2021. I was burned out, juggling two part-time jobs, trying to plan a wedding, and drowning in full-time job applications. I felt overwhelmed and underprepared as I plunged into a sea of candidates I perceived to be more intelligent and better "fits" than me. My portfolio was full of the usual Titanic, Iris,...