Want to be the brains behind the next ChatGPT?

11 || May || 2024

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#Issue 65

How to become
a data engineer

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Hello ET people👋🏾

Welcome to the third and last edition of our series on entering tech as a data professional. In the past two editions, data professionals shared how newbies can become data analysts and data scientists

Today, we will be treating the least popular of the trio, data engineering. Like back-end developers, data engineers don’t often enjoy the spotlight, even though they do very important work that makes it possible for generative AI like ChatGPT to exist today. So next time you see a data engineer, don’t be scared, just give them a polite nod and maybe offer a fist bump. They’re not used to attention. 

Let’s dig in.

by Faith Omoniyi & Timi Odueso

How data engineering works

Businesses need large amounts of data to make informed decisions. This data is often available only in raw formats and is hard to make sense of. 

Data engineers collect this unprocessed data and turn it into actionable and usable information for data scientists, data analysts, and business analysts, who use it to make business decisions. Data engineers are the unsung heroes, as they make it easier for data scientists and analysts to earn a living. 

Data engineers wear many hats! They source datasets relevant to business goals, develop algorithms to transform raw data into insights, design and maintain data pipelines, collaborate with management to understand needs, create new data validation methods and analysis tools, and ensure everything complies with data governance and security policies.

Too many tasks, you might say; remember, they are heroes, right? 

Before we go further, let’s tell the story of Adeolu Adegboye, who leveraged his data science background to transition into data engineering. Adeolu started learning data science when he thought the world was ending during the COVID-19 lockdown. In 2021, he got an internship as a data scientist and then transitioned to data engineering in 2022 because engineering had always winked at him.

Adeolu Adegboye

Who is a data engineer: Coursera defines data engineering as the practice of designing and building systems for collecting, storing, and analysing data at scale.

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What you need to become a data engineer?

Here’s what the typical career path of a data engineer looks like: Data Engineer ➡️ Mid-Level Data Engineer ➡️ Senior Data Engineer ➡️ Data Architect/Lead Data Engineer/Data Engineering Manager.

Data engineering is a purely technical field that requires programming knowledge of Python and SQL, along with skills in data modelling, ETL, data management, and data architecture. Adeolu strongly recommends that prospective engineers be versed in the different cloud computing platforms—Amazon Web Services (AWS), Microsoft Azure, and the Google Cloud Platform (GCP).

According to him, data engineering is a holistic skill that requires learning a bit about everything, from database handling to analytical reasoning, machine learning, data security, data storage, and so on.

On the soft skill rung of the ladder, problem-solving, communications and stakeholder management are the most important skills. Data engineers are required to ensure the end user/client understands the full context of what the data provided can do for them. 

Meme Source: Zikoko Memes

If you’re wondering where you ca learn data engineering, Adeolu recommends that you follow the 100-day plan for newbies in data engineering by The Seattle Data Guy. He teaches a range of topics and provides a spreadsheet that houses over 50 courses, challenges, and materials. Adeolu claims that if followed religiously, the 100-day plan could potentially land you an internship or even a full time role if you’re a badass. 

Data professionals I have spoken with for this series say Data Camp is a safe haven, if not heaven, for data professionals. Courses on the platform are made by data professionals and cater to different phases of your learning journey. While courses on DataCamp are priced, Adeolu recommends free alternatives on Codecademy and Coursera. 

Below are some of his recommendations. 

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You can learn data engineering too

IBM Introduction to Data Engineering

Learn the basic skills required for an entry-level data engineering role.

  • Price: Free
  • Duration: 1 – 4 weeks
  • Tools Needed: Laptop + internet access
  • Level: Beginner
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IBM Data Engineering Foundations Specialization

Learn the Working knowledge of Data Engineering Ecosystem and Lifecycle. Viewpoints and tips from Data professionals on starting a career in this domain.

  • Price: Free
  • Duration: 2 months (at 10 hours a week)
  • Tools Needed: Laptop + internet access
  • Level: Beginner
Get Course
Introduction to Relational Databases (RDBMS)

Learn how to describe data, databases, relational databases, and cloud databases as well as information, data models, relational databases, and relational model concepts (including schemas and tables).

  • Price: Free
  • Duration: Flexible schedule (15 hours approximately)
  • Tools Needed: Laptop+ internet access
  • Level: Beginner
Get Course
Data Engineering on Google Cloud

This programme provides the skills you need to advance your career and provides training to support your preparation for the industry-recognized Google Cloud Professional Data Engineer.

  • Price: Free
  • Duration: 1 month (at 10 hours a week)
  • Tools Needed: Laptop+ internet access
  • Level: Beginner
Get Course

How to land your first role

However, if you are looking to take a stab at it right away, Adeolu claims that following the 100-day plan mentioned earlier by The Seattle Data Guy can land you an internship or an entry-level job. If you’re not planning on going through that route, we have some other tips for you. 

As we have recommended in other episodes, getting your first role as a data professional is not rocket science. The short answer is: put yourself out there, send out cold emails or messages, have a tailor-made CV, join great communities, and attend job fairs and industry events.

Adeolu also recommends documenting your learning journey—on Substack or Medium—and sharing it on social media as a surefire tip for getting noticed in the data engineering field. Applying for freelance and volunteer projects on sites like Omdena is a great way to build your portfolio. 

GIF Source: Reddit

They say you are the average of the five people you spend the most time with. But I’d say finding the right community is like finding the perfect pair of jeans. Joseph Ojo, a data engineer at Nomba, a Nigerian fintech, says joining a community is the best way to upskill and discover new trends—and even job opportunities as a newbie. He recommends joining communities like Young Data Professionals (an invite-only community) and Data Engineering community.

To stay updated on the latest industry trends, Joseph recommends living partially on Medium and subscribing to relevant newsletters like

We hope we have been able to stir you on the path of becoming a badass data engineer hero! To connect with Adeolu, you can reach him on LinkedIn. See you in the next edition! 

P.S. You can also share feedback—or a shoutout—with us about this edition by sending an email to newsletter@techcabal.com. Did we leave something out? Is there something else you’d like to read? Let us know! It helps us write even better editions.

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Faith Omoniyi Reporter
Timi Odueso Senior Editor, Newsletters

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