- Interesting Data Gigs by Marcos Ortiz
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- Interesting Data Gigs # 1: Featured Job of the Week: Data Engineer at Cash App; Why you must follow Daniel Lee and Caleb Keller and more...
Interesting Data Gigs # 1: Featured Job of the Week: Data Engineer at Cash App; Why you must follow Daniel Lee and Caleb Keller and more...
Welcome to the first edition of Interesting Data Gigs
🚨 Join the Interesting Data Gigs Talent Network 🚨
It’s the perfect time to be part of The Interesting Data Gigs Talent Network, where you will find amazing Data Analytics jobs from companies like Netflix, Apple, Consensys, and many more.
Let’s change the game together: Instead of people applying to companies, companies will pitch to you, so don’t wait any other moment and join today.
I'm a man of my words, so today I'm officially launching the first edition of Interesting Data Gigs, a newsletter (and soon a talent network) fully dedicated to helping people with Data-related jobs to find their dream job.
That's our mission here, and we will work hard to achieve that mission.
The core idea of the newsletter is to highlight a Data-related job and help them to make deep research on the role and the company you will apply for, with the goal to spark some ideas in your mind, and do a better job applying for it.
I've done this in the past; you could read here or here, and you will see what I'm talking about.
This newsletter will be cross-posted here and on LinkedIn, so if you want to subscribe to both places, you can do it here.
So, this newsletter is not about me, it’s about you.
Time to provide value since day one.
Featured Job of the Week: Data Engineer at Cash App
First, you can find the job post here.
My first advice is always to try to know as much as possible about the company, its business model, the main challenges they could have on the way, and more.
First, research the company you are applying for
So, in order to do this with Cash App, first, you should read this interesting post from Rex Woodbury (Partner at Index Ventures) called The Rise of Cash App, in his weekly publication called Digital Native.
Rex described why Cash App has grown exponentially in recent years, to the point that it’s the # 1 Finance App in the App Store for 5 years, and it’s the 8th most downloaded app in the United States in 2021, reaching 80 million users.
You can read the presentation they made to its investors in 2021 here.
Cash app is part of Block (formerly known as Square), so it’s a subsidiary of a public company.
Some people argued with me that we don’t have to know the numbers of the company.
DON’T LISTEN TO THAT ADVICE.
You must know the financial health of the company, especially with so many companies doing layoffs now.
So, take your time and at least, read the presentations they made for the shareholders of the company.
You can discover so much information just by doing that.
For example, you can watch the last presentation that Amritha Ahuja (Block’s Chief Financial Officer), and Brian Grassadonia (Cash App Lead) gave at the Credit Suisse TMT Conference or the last presentation that Brian gave on the Block Investor Day, which contains a trove of information:
A very interesting fact that Rex shared is this one:
Cash App acts like a social network because it is a social network. Cash App sees a 31 percentage point increase in retention when a user has 4+ friends on the app. The product is designed to integrate social features, which in turn improve unit economics.
You have to understand all this if you want to stand out in your application.
Next stage? The Cash App’s Data Tech Stack
According to the job post, they are using this:
Snowflake for Data Warehousing. Read how they are using Snowflake here
Fivetran for ETL. Block has 14k ETLs, according to this post from Amogh Kambale
Apache Airflow for orchestration according to this post
SQL everywhere
Experience with major cloud platforms like Google Cloud Platform or Amazon Web Services
Python or R
Bank risk knowledge
Next stage? Data Engineering people at Cash App
It’s not about requesting a referral (if you do it, good for you), it’s about establishing a bond with these people, even before starting at the company.
Your curiosity could be your ally here, but please, be respectful.
Some people you could contact here:
David Grochowski, Engineering Manager at Cash App
Aditya Nagpal, Business Intelligence Data Engineering Manager at Cash App
Liz Savage, Data Engineer at Cash App
Danielle Carollo, Data Engineer at Cash App
Now, it’s up to you my friend.
Good luck with your job application.
Other Interesting Data Gigs of the week
Why you must follow the work of Daniel Lee and Caleb Keller
This newsletter is not about jobs, it’s about people.
For that reason, in every edition, I will highlight the work of at least two amazing people who are creating content and helping a lot of folks out there to do a better job as Data Analysts, Data Engineers, Data Scientists, and more.
Let’s talk about the first one: Daniel Lee.
Daniel has created an amazing website called DataInterview.com, where he has shared a lot of mock interview videos for specific roles in companies like Amazon, Netflix, PayPal, Google, Meta, and many more; where you could practice a lot.
You can see one of these videos on his YouTube channel for Amazon Business Intelligence Engineer:
or this one for Facebook Data Scientist:
Daniel always provides great feedback on these mock interviews, so make sure you watch the videos completely.
Let’s talk about Caleb Keller now.
Caleb is focused on Jupyter notebooks, and he is sharing a ton of great tips on LinkedIn and his own website, about organizing your code inside your notebooks, how to make them more readable and extendible, and many more amazing tips.
You can see one of his posts here.
So, you must follow him on LinkedIn now.
Interesting links to read to keep improving your Data Engineering knowledge
The last section of every edition will focus on great links out there. Enjoy your reading:
Lessons Learned From Running Apache Airflow at Scale, by Megan Parker from Shopify
AlloyDB for PostgreSQL under the hood: Columnar Engine, by Sheshadri Ranganath, Engineering Director at Google
How Vimeo Keeps Data Intact with 85B Events Per Month, by the Firebolt team
Ingest Stripe data in a fast and reliable way using Stripe Data Pipeline for Amazon Redshift, by Jessica Ho and Alexander Mahabir from Amazon Web Services
Debuggable Airflow TaskFlow ETL snippet for VS Code, by Abbas Allahyari, Data Scientist at Elin
BigQuery Explainable AI now in GA to help to interpret your machine learning models, by Xi Cheng and Polong Lin from Google
Final words
Love to hear your feedback in this edition, and remember, the next stage of this is to build a talent network.
If you want to be part of it, subscribe to this newsletter on Substack:
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