Top data engineering writer on Medium & Senior Data Engineer in media; I use my skills as a former journalist to demystify data science/programming concepts so beginners to professionals can target, land and excel in data-driven roles.
[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 |
Pipeline To DE
Top data engineering writer on Medium & Senior Data Engineer in media; I use my skills as a former journalist to demystify data science/programming concepts so beginners to professionals can target, land and excel in data-driven roles.
Extract. Transform. Read. A newsletter from Pipeline Hi past, present or future data professional! When you apply to data analysis, data engineering or data science jobs, you likely consider factors like company name, culture and compensation. Caught up in the excitement of a fresh opportunity or compelling offer you’re neglecting an important part of your day-to-day reality in a new role: What stage of data maturity the organization is in. If you’re looking for experience building something...
Extract. Transform. Read. A newsletter from Pipeline Sponsored by Basejump AI. Don't just query your data; chat with it. Learn more. Hi past, present or future data professional! If you’re a hybrid or remote worker (or online student) you know the FOMO that sets in when you leave your desk and something at work needs your immediate attention. Even though data engineering is a role that can be done from anywhere, having to open, set up and position a laptop isn’t ideal in all situations like...
Extract. Transform. Read. A newsletter from Pipeline: Your Data Engineering Resource Presented by Basejump AI Use natural language prompts to chat with your database in Basejump’s intuitive interface, or embed it directly in your application. Book your demo here. Hi past, present or future data professional! One thing that makes my work day easier is when I’m Google-ing (as all software developers do) a problem and I come across the holy grail of solutions: A one-line implementation. Like...