Interesting Data Gigs # 6: Data Engineer I at ZoomInfo (NASDAQ: ZI)

Why you must follow Julia Silge and Lex Fridman

June 21, 2022

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Hi Data Geeks.

Today, I will be talking about ZoomInfo (NASDAQ: ZI), well known as the “Go-To Market Platform“ and a very interesting public company with an amazing business model, looking for incredible Data-Driven people to join the team.

Why you should join ZoomInfo

The position I will be talking about is Data Engineer I, and the POC here is Joseph Russo.

Let's take the profitability test first:

  • is ZoomInfo profitable? YES. According to its last financial results in Q1 2022, the company generated $241 Million in revenue (an increase of 58%), an Unlevered Free Cash Flow of $125.9 million, and a Cash and Cash Equivalents amount of $394 Million. So, it’s highly profitable and with a good cash reserve on hand. ✅

ZoomInfo’s Data Tech Stack

If you read carefully again the job post, you will see that the tech stack is very interesting as well:

So, if you are working right now with all these tools, I encourage you to apply for the position or at least have a conversation with Joseph about it.

Let’s dissect the job here and discuss some ideas on how to approach this job application (THE REAL MEAT)

First, don’t forget to read these interesting resources in the ZoomInfo’s Engineering blog:

Second, if you read the role, you should know at this point that the company is actively using Amazon Web Services and Google Cloud Platform.

Why?

Because they are where the data of their clients is needed, and some clients use AWS and others use GCP, some clients use Snowflake for its data efforts, others use BigQuery. You can see all the integrations that ZoomInfo has when you visit the ZoomInfo’s Apps Market:

ZoomInfo’s Apps Market

So, if are a Data Engineer who has worked with at least two major cloud providers, you are in a very good position to do this application. Even better if you have used different Big Data or Data Analytics related products in both of them.

In one of the items of the job description, they put the “Nice to Have“ points:

  • Hands-on experience in Python or equivalent programming language

  • Experience with Airflow and DBT

  • Experience with AWS/GCP cloud services such as GCS/S3, Lambda/Cloud Function, EMR/Dataproc, Glue/Dataflow, Athena.

  • Experience with data visualization tools and infrastructures (like Tableau/Sisense/Looker/other)

  • Experience with development practices – Agile, CI/CD, TDD..

So, you get the idea.

My advice here? Pick a cloud provider and become an expert in the tools they are using right now.

For example: let’s say you want to specialize in Google Cloud Platform, so pick the tools from GCP like Google Cloud Storage, GCP Dataflow, Dataproc, and of course BigQuery, and become “the expert“, even before applying for it.

And especially how to combine all these services to create Data-driven solutions.

How to do that?

The second piece of advice here is simple but powerful: make sure that your solutions are very efficient related to costs vs value and impact.

ZoomInfo started its journey as a bootstrapped business, so you should know that they are very sensitive to costs, and if you can think about this even from the start of the design of your Data Engineering pipelines, do it.

How do to do that with Google Cloud?

Make sure to read the work of Pathik Sharma, the Cloud FinOps Cost Optimization Practice Lead at Google Cloud, especially these resources:

Using these tips, you could combine the knowledge you already have in the Data Engineering front, with a FinOps approach for everything you will be doing at ZoomInfo.

This could give you an edge, at least from my perspective.

So, again if you are interested in the position, chat with Joseph Russo.

Other featured jobs of the Interesting Data Gigs Jobs Board

People to follow: Julia Silge and Lex Fridman

The content of both of them on LinkedIn related to Artificial Intelligence, Data Science, R, Data Visualization, and more is simply amazing

For example, Julia has an interesting hashtag called #TidyTuesday where she shares interesting research, insights, or visualization for a particular problem using the Tidy framework from R.

The last one was focused on how to use the spatialsample package to understand drought in Texas, and how it is related to other characteristics of TX counties:

You can check that code on her blog as well here.

In the case of Lex, the real jewel is his podcast, where he invites incredible people to chat about different topics.

One of my favorite episodes was the conversation with Tony Fadell, the co-creator of the iPod, iPhone, and the Nest thermostat; where they chatted about the new book written by Tony called “Build: An Unorthodox Guide to Making Things Worth Making”.

You can watch the entire conversation here:

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