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 #13] A 3-Step Python Script To Write Less Cover Letters
Extract. Transform. Read.A newsletter from Pipeline: Your Data Engineering ResourceHi past, present or future data professional! Somewhere along your professional development journey someone lied to you. They told you to crank out resumes because no one reads cover letters. This couldn’t be further from the truth as 87% of hiring managers read cover letters. Such a high read rate represents a compelling opportunity to sell your data skills and showcase a bit of personality. The problem? Those pesky 3 paragraphs take way too long to write—as long as 30 minutes per job. Assuming you’re applying to 3-5 jobs per day, you’re looking at 2.5 hours of cover writing time. Earlier this year, while helping a friend apply for data science positions, I created a simple Python script to auto-generate cover letters based on input. In addition to generating a cover letter based on my more than 500 hours as a career advisor, it will convert your output to a PDF, the preferred format for cover letters and resumes. Even if this helps you generate cover letters faster, you might want to think twice about “spamming” your resume/cover letter. Only use a bulk application method if:
Since I’m not trying to ask you to spend 30 minutes on this email, here are this week’s links:
Finally, this week is significant to me because 9/13 marks 3 years in data engineering. Read my story and advice for following a similar path. Why I Nearly Turned Down A 30k Raise And A Data Engineering Job Questions? You know where to find me: zach@pipelinetode.com. Until next time - 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 PipelineToDE Hi past, present or future data professional! If you’re a job seeker in the data space, your GitHub portfolio has only one job: To act as a calling card that gets you to the next step of the hiring process. Too often, I review portfolios for potential referrals and see brilliant code buried under structural mistakes that have nothing to do with programming skill. Your GitHub is not just cloud storage for your code; it’s a public display...
Extract. Transform. Read. A newsletter from PipelineToDE Hi past, present or future data professional! Despite crushing autocorrect scenarios, most AI code assistants like CoPilot miss a critical step when helping developers of any experience level: Validation. Arguably, leveraging an AI Agent to validate a code’s quality is on the user. But a surprising amount of experienced programmers are taking the worrying approach of believing an AI’s first “thought” when it comes to code that will...
Extract. Transform. Read. A newsletter from Pipeline Hi past, present or future data professional! A data science manager recently gave me some blunt, liberating advice over coffee: “If a team lead really cares what cloud technology you know (AWS, GCP, etc.) and doesn’t consider transferable experience… run.” This critical advice, which informs the conclusion of my soon-to-be-released ebook on data engineering project development, cuts to the core of a major problem in data hiring: The...