Top companies hiring data engineers in 2023

Your go-to guide for finding the best companies hiring data engineers this year. Learn what skills you need, which industries are in high demand, and tips for the application process.

Data engineering—have you heard of it? Chances are if you're reading this article, you're either in the field or aspiring to break into it. In a world awash with data, who's behind the scenes making sense of all the numbers, characters, and bytes? Well, that would be you, the data engineers.

This article aims to guide you through the labyrinth of job opportunities and help you find the best companies hiring data engineers in 2023. Salary, culture, growth—you name it, we cover it.

The rise of data engineering

First things first, let's talk about how crucial your role is. Remember the time when businesses managed their data in Excel sheets? Yeah, those days are long gone. Now, it's all about big data, cloud computing, and AI-driven insights.

What is data engineering?

Imagine a raw diamond. Beautiful, but not very useful in its current form. A data engineer is like a skilled artisan who cuts and polishes this diamond to make it truly valuable. Essentially, you take raw data and transform it into a format that can be utilized by data scientists or analysts. You're the first part of the data pipeline, so if you mess up, everything downstream gets impacted. No pressure, right?

The importance of data engineering in business

Think of data as the new oil. Just like oil needs to be refined to produce gasoline, data needs to be processed to produce actionable insights. Companies rely heavily on data engineers to construct a robust data infrastructure that can support their decision-making process. Not convinced? A single error in data management can cost companies millions of dollars. It's that serious.

Qualities companies look for in a data engineer

Let's get down to brass tacks. If you're on the hunt for a job, you ought to know what you're being judged on.

Technical skills

Obviously, you'll need to know your Python from your Java. Familiarity with big data tools like Hadoop and Spark is often a must. SQL? That's your bread and butter. The more programming languages and tools you master, the more irresistible you become to employers.

Soft skills

Can you play well with others? Teamwork and communication skills are crucial in any workplace, and data engineering is no exception. You'll often be working in interdisciplinary teams, so the ability to convey complex technical ideas in simple terms is invaluable. Remember, you're a bridge between the data and the decision-makers.

Experience and certifications

Got a few years of experience under your belt? Great. New to the field? That's alright, too. Companies often value a mix of experience and fresh perspectives. Certifications can also make you more appealing. Whether it's a degree in computer science or a specialized course in data engineering, every bit helps.

Top sectors hiring data engineers

So where's the buzz? Where should you be applying? Let's break it down.


No surprises here. Tech companies are swimming in data. From giants like Google and Amazon to upcoming startups, there's a constant demand for data engineers.


Think about it. Patient records, treatment plans, medication data—the healthcare industry is teeming with data that needs to be managed and analyzed.


If there's one sector that's synonymous with data, it's finance. Stock markets, trading, risk assessment—you get the picture. Banks and hedge funds are on the constant lookout for data engineers.


With the rise of e-commerce, retailers are relying more on data to drive sales, manage inventory, and predict consumer behavior. Ever wondered how Amazon knows exactly what you want? Now you know.

This concludes the first part of the article. If you'd like me to continue writing, please let me know!

What to consider when choosing a company

You've got the skills, you've targeted the sectors, but how do you choose the right company for you? Let's get real for a moment. A job isn't just about the paycheck.

Work-life balance

Are you a 9-to-5 kind of person, or do you not mind burning the midnight oil? Companies have different cultures, and it's crucial to find one that aligns with your lifestyle. Remember, work is a marathon, not a sprint.

Company culture

Are you a square peg trying to fit into a round hole? That's what it feels like when you're in a company whose culture doesn't align with your values. Whether it's a laid-back environment or a high-octane, competitive atmosphere, make sure you know what you're getting into.

Growth opportunities

The tech world is ever-changing, and you don't want to get left behind. Does the company invest in training and development? Is there room for upward mobility? Don't be the hamster on a wheel; make sure you're going somewhere.

How to apply

You've got your eye on the prize. Now, how do you go about getting it?

Resume preparation

Your resume is your ticket to the interview room. Make sure it showcases not just your skills but also your achievements. Did you help increase efficiency by 30% at your last job? Put it in there.


Ah, the dreaded interviews. It's not just about answering questions; it's also your chance to interview the company. Ask about the team, the projects, the coffee—anything that will give you a sense of the place.


If you've read this far, you're serious about finding the right data engineering job in 2023. It's not just about having the technical chops; it's also about finding a company that aligns with your personal and professional goals. So go ahead, take the plunge. Your dream job is out there, waiting for you to click 'apply.'

Join millions of Data Experts

The ratio of hired Data Analysts is expected to grow by 25% from 2020 to 2030 (Bureau of Labor & Statistics).
Data Analyst is and will be one of the most in-demand jobs for the decade to come.
16% of all US jobs will be replaced by AI and Machine Learning by 2030 (Forrester).
© 2023 | All Rights Reserved | Built with 🤍 in MontrealAll our data is gathered from publicly available sources or contributed by users