The State of the 2026 Data Engineering Job Market
The State of the 2026 Data Engineering Job Market
And how to get hired with an AI Data Engineering project on Databricks
The job market in 2026 is bad. It’s been bad since the end of 2022.
That being said, people are still getting hired, but it requires a lot more effort.
In this article, we will talk about,
How is the big tech job market different from the overall software engineering job market?
Are data engineering jobs more impacted or less impacted by AI?
What can you do to stand out and land an offer in 2026 (including building a full-stack AI application on Databricks Free Edition)
Big Tech != overall job market
If you’ve been watching the news, you might be under the impression that everybody is losing their jobs. And there’s good reason for you to think that!
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Netflix just laid off 1,000 people on October 14th
Uber cut 3300 people in September
Meta laid off over 8000 people in May
If you want to track all of these layoffs, there’s a really cool tool called CodeSunset here.
Depending on your definition of “big tech,” about 5-10% of engineers in the United States work for one of those companies.
So what’s happening to the other 90% of engineers? It’s more complicated than just a layoff bloodbath. These engineers are experiencing three things:
Their jobs are pretty stable, but employers are reluctant to add headcount. They’re seeing demands from employers to basically do two engineers’ jobs, leveraging the power of AI.
Junior engineers are having an incredibly hard time breaking into the market.
Employers no longer want data engineers who just know SQL, Python, and Airflow. They must know how to build AI-enabled systems!
This is why I partnered with Databricks to create the free course Rise of the AI Data Engineer. In this course, you will use Databricks Free Edition to build an end-to-end AI stock trading app over 6 hours of labs.
Are data engineers more impacted by layoffs and AI?
If you dig into the data from The Uptime Report, you see the following:
Software engineering jobs are down ~22% from their pre-pandemic levels
Data & Analytics jobs are down ~36% from their pre-pandemicd levels
Data engineering sits at the annoying intersection of software engineering and data, so it’s hard to capture very detailed evidence about it. So looking at the data cut across sectors isn’t that helpful!
As a helpful reminder, there are approximately 8 to 10 times more analysts than data engineers in the United States. So, about 80-90% of the drop must be attributed to the death of traditional data analyst jobs. (Tools like Databricks Genie dramatically speed up data analytics as well as lower the barrier to entry).
My view on this 36% drop is that it’s a difficult time to be a data analyst, and data engineers are too small a percentage of that pie to know what is actually going on for them from this data set.
Gone are the days when you can learn SQL + Tableau and make $100k+. We must upskill and learn how to leverage AI!
The Get U Hired Report for October 2026 is a little bit more encouraging and specific!
We’ve seen continuous data engineering job growth from August through October.
But only 5.5% of those roles are for juniors! This is especially alarming given that data analyst roles are getting harder to come by.
Going from junior data analyst to data engineer is a common transition in industry, historically speaking, and it’s what I did back in 2015 to get my first data engineering role!
Despite what the Claude code bros will tell you, the fundamentals of data engineering still matter! But also adding hot technologies like Databricks, dbt, AWS, and others
The skills that actually matter to get a data engineering job in 2026
Data engineering hiring is showing encouraging signs of growth in 2026. One industry research report estimates that data engineer job postings are up approximately 35% year over year.
But what about the fancy “forward deployed engineer” jobs that everybody is talking about? That role is growing by 500% year-over-year. But the 500% is from an extremely tiny base. There is a lot of promise in those roles, but they require another layer of skill set, which is mastering agentic AI!
So in summary, data engineering is more difficult to get into than it was in 2021. Zero-interest-rate Oprah isn’t out here giving everyone jobs anymore. But it’s not impossible to get a data engineering job in 2026 either. (Although it may feel impossible if you’re a junior) We all understand the market is more competitive. So how do we actually stand out? How do we make sure our resume is selected? How do we survive the interview?
What can you do to stand out and land an offer in 2026?
AI has created a blast of noise in the job market. (LinkedIn adding the Easy Apply button didn’t help either). It is rather phenomenal that it is possible to apply to tens of thousands of jobs using AI agents in 2026!
Employers are demanding AI skills, and every candidate has the same boring RAG chatbot example project. Their project isn’t deployed anywhere for recruiters to check out either!
So how can you build a project that actually stands out?
It should have 3 pieces to it:
A live URL that they can check out. Databricks Free Edition allows you to deploy applications for free.
After setting up your Databricks account, in Day 1 of the course you will set up your Databricks app and Postgres server
A data pipeline that generates context for your AI agent to make better decisions with
In Day 2 of the course, you will set up Spark data pipelines that generate rich vector context within Lakebase. The pipelines will then scrape stock market information so our AI Agent in Day 3 can make trades.
An AI agent that actually makes decisions and actions that change something
In Day 3 of the course, you will need an Alpaca Markets account, then you will be building an AI agent with Agent Bricks that reads the context from Day 2 and makes stock market trades off the information that was scraped!
Having a project that isn’t just a simple RAG chatbot and that actually makes real actions is how you get further in the interview funnel!
Make sure to join the DataExpert community Discord to find other people like you who are motivated to learn!
Once you have a good project and skills, you need to start finding your opportunities.
Easy applying on LinkedIn is the worst way to apply for jobs. You can try to win on volume like that, but you’ll probably be very disappointed and be like those people on the internet who are like, “I applied to 15,000 jobs and got ghosted or rejected every time”
So how do you raise the signal of your application?
Choose another avenue besides LinkedIn.
Maybe a career fair?
Maybe a warm intro from a friend or past colleague?
Maybe the DataExpert Community?
The key thing here is to try many different avenues to test what actually gets you interviews.
Make sure to always feed the job description and your resume to AI and have it tailor your resume to the job description to maximize the chance that you don’t get filtered out immediately. (This feels weird because it’s AI vs AI, but not doing this also feels like leaving advantage on the table)
Once you get the interview, follow this guide to actually approach the interviews with confidence!
Please comment what other things I missed that have helped you get a job in 2026 and make sure to share this with your friends!
The job market is really challenging out there! I believe in you!
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© 2026 Zach Wilson