193: My HONEST Thoughts on The Data Job Market in 2026

Speaker: 00:00:00

Avery Smith-1: If you're breaking

into data analytics right now, you're

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probably pretty depressed and pretty

anxious with everything that's going on.

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: 00:00:05

It feels like there's no data jobs left.

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: 00:00:07

The few data jobs that are left are

uber competitive, and the rest of

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: 00:00:10

the data world is just going to be

replaced by AI by the end of the year.

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: 00:00:14

If you feel this way, I don't blame you.

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It's super easy to fail this way in

today's market, but I'm going to share

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some raw, transparent numbers that

I think is gonna give you a little

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bit of hope and a little bit more

insights to what the data market is.

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Actually like right now and what

you can expect moving forward.

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The first question you probably

have is, are data rolls die?

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And the answer is no, but a lot

of them aren't growing either.

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Let me explain.

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So this chart right here shows the growth

of data rolls over the last four years.

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You see that data engineer

roles have grown 49%.

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Data analyst roles have grown about 12.6%,

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and data scientists

have grown about 11.7%.

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What this basically means is if there was

a hundred data engineers, data analysts

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and data scientists, at the end of 2021,

there is now 149 data engineers, 113

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data analysts and 112 data scientists.

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And so your first thought might

be, wow, look at data engineers.

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Like they have grown a lot and the

answer is yeah, they've grown a ton.

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And one of the reasons why is ai, AI is

only as good as the data you feed it.

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And data engineers are really good at

storing big data and cleaning big data.

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And that's exactly the type of

things that AI companies need

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to actually make useful models.

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So that's one of the reasons why we see

a really big growth of data engineers.

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The other reason I think we're

seeing a big growth of data

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engineers is we overhyped data

analysts and data scientists.

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The data scientists role was actually

voted the most sexy data title of.

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The 21st century.

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And the answer is, data science is

really cool, but it, once again, if

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you don't have really structured,

really clean, well stored data,

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you can't actually do that much.

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And so data engineers basically

didn't exist 10 years ago really, as

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at least the way that they do today.

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And so we were trying to do all

these really cool data analytics

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and data science projects

without proper data engineering.

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And that led to a lot of data

science projects failing.

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Now we're kind of going backwards

as a society and being like,

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okay, we need data engineering.

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We need data engineers to build the

fundamentals of a good foundation that

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we can actually build our data analytics

and data science projects on top of.

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So I think we had a little bit of

false, like mega growth for data science

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and analytics in the past decade.

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And now data engineering is

just kind of catching up.

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Now.

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It is important to actually

realize this is growth.

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This is actually raw numbers.

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So right now there's actually.

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51,000 open data analyst jobs

on LinkedIn across the world.

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And there's only 25,000 open

data engineer jobs and even less

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13,000 open data scientist jobs.

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So although data engineer has grown

quite a bit in the last four years,

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it's still nowhere as large as the

number of data analyst jobs that

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are open in the world right now.

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Now let's talk about the data

analyst and the data scientist

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role over the last four years.

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Growth has kind of become

stagnant in the last two years.

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Now why is that?

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There's lots of options.

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You could argue that AI is the reason, but

for me, once again, I think companies are

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investing in their data organizations, but

specifically they're putting an emphasis

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on the data engineering because they

know if they get the data engineering

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right, and they do that well, the data

analytics and data science teams and

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projects will kind of follow after that.

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Also, I think it's important to

realize that there's a lot of

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pressures going on in the world.

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Specifically what I know is the us

there's like a crazy political thing

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going on where there's tariffs.

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No, there's not tariffs,

there's visas, there's no visas.

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Like the stock market is

up and down every day.

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Like things are a little bit tight.

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It feels like we're gonna have

a recession or a financial crash

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soon, but it hasn't happened.

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I've been waiting years for it to

dip down, so I could buy the dip,

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but it just keeps going up and up.

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So I think to stay stagnant

isn't actually necessarily bad.

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There's not less data jobs, it's just

like we're in a weird place where

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we're trying to see what's happening.

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Now personally, if I'm being

100% honest and transparent.

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I really see this trend continuing

through the rest of this year.

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For the most part, I think a lot of

companies will still put most of their

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investment into data engineering to

try to get that sound foundation.

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Although I could see a lot of

companies have already done that, and

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so you might see a slight uptick in

data analysts just because there's

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quick wins for data analysts to

have once that foundation is laid.

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By the way, this is the type of analysis

graphs and data that I try to share

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every week in my newsletter that's

specifically for data professionals.

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It's a hundred percent

free and it's 25,000.

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: 00:04:06

Other aspiring data professionals have

already joined, so why not join them?

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Go to data career jumpstart.com/newsletter

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or click the link, the

description down below.

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The next question you might be asking

is, well, there's no data jobs left.

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What companies are even

still hiring data analysts?

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And you might think it's the FANG

companies, but really it's not.

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So who are the companies

hiring the most data analysts?

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Well, this chart right here basically

shows you the top 20 companies that

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hired data analysts in the previous year.

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And number one, we have

Accenture two, Amazon three,

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McKenzie four, Deloitte, five C.

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Six American Express seven, capital

one eight Tata Consultancy, uh, nine

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Cognizant and 10, uh, TD Ameritrade.

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You can read the rest

of the list down below.

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Now, if you really analyze this list,

what you'll notice is most of these

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companies are either consulting companies

or financial service companies and bank.

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And that's really important to realize

because a lot of people think in

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order to work for data companies,

you have to work for like Microsoft

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or like Google or like Apple, and

that's really just not the truth.

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Obviously the tech companies are really

cool and they have cool products,

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but there's so many companies.

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Basically every company needs.

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Data people, they need people to

look at the numbers to actually make

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data-driven decisions for their business,

whether they're a hospital or a bank,

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or even like a mom and pop shop, like

data analysts are needed everywhere.

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So although you might really wanna

work for a tech company, and tech

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companies are cool, just remember

there's so many other options out there.

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And my suggestion is really to probably

focus on these consulting and financial

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service companies because these are

the people who are looking like they're

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dedicated to paying and hiring data

professionals moving forward in this

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challenging, tight economic time.

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And at this point you might be

wondering, well, Avery, where

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did you get all of this data?

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Like is it even valid?

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And the answer is, I got it from a

company called Live Data Technologies.

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They're a data product, and if you listen

to an episode that I released recently,

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or you're subscribed to my newsletter,

you learned what a data product is.

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But basically they sell data as a service

and they're tracking working professionals

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in real time so that you can actually

see where people are going, how companies

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are shifting, what roles are going up,

what roles are going down, what companies

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are actually hiring, what companies

are firing, those types of things.

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And they were actually kind enough

to send this data to me and let

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me share it with all of you.

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So if you wanna learn more about

them, you can check their link

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in the show notes down below.

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Next, I have a lot of people come up to me

on LinkedIn or in person and they'll say,

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Hey, Avery, tech roles, they're cooked,

meta just laid off this many people.

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Intel just did 20,000 layoffs,

like with no warning whatsoever.

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It's over for data jobs,

it's over for tech jobs.

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But here's the truth, you might be

missing once again, the big F companies.

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They dominate the headlines.

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Yes, they're the biggest companies

and maybe they're the most

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important to the US economy.

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Sure.

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But there's still thousands of

other companies who are hiring

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data people all the time who maybe

aren't laying anyone off right now

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who are maybe hiring right now.

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And to illustrate this, I'd

like to actually share a

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personal story of layoffs that.

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Completely affected my life

and is probably the reason

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I'm here talking to you.

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This chart right here is comparing and

contrasting the stock price of ExxonMobil

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to the stock price of meta or the stock

price of Facebook from: 2019

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And the reason I'm showing you this

is at the time I was actually employed

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at ExxonMobil as a data scientist.

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We had layoffs.

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My own team had layoffs and everyone

on my team was like, oh my gosh,

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ExxonMobil, it's going in the pooper.

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It stinks.

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It's a bad company.

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Look at Meta Meta's basically

doubled their stock price recently.

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We need to get out of oil, we

need to get outta manufacturing.

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We need to get to big tech.

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'cause they're hiring so

many people right now.

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Their stock price is doing so well.

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Our stock price stinks.

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You know, we're on the decline.

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Everything's gonna go terribly.

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We should all leave and

we should go to meta.

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Now, watch what happened in 2021 and see

if we were right or if we were wrong.

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At the beginning of 2021, meta stock was

doing fine, but then it took a huge dive

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and basically lost 50% of their value.

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Meta had a ton of layoffs this year while

ExxonMobil doubled their stock price

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back to basically what it was originally.

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Now, Exxon was hiring data scientists

and Meta was laying off data scientists.

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The point here is if a company's

laying people off, you don't know

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if that's going to magically just

be the opposite the next year.

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And even if layoffs are happening

in the tech industry or whatever

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industry, there's probably another

industry that is booming that needs to

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hire data scientists, data engineers,

data analysts, data scientists.

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They're needed in every industry.

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Financing, consulting, manufacturing,

tech, like literally every

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industry needs data professionals.

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And just because the FANG companies

are laying people off doesn't mean

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that other companies, for instance,

like ExxonMobil aren't hiring.

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Let's flip over to 2023 to today, and

sure enough, meta, even though it seems

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like they might even do layoffs right

now, has four x their stock price and

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ExxonMobil is staying pretty steady.

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They're up about 20% still, and they're

still hiring at a very sustainable pace.

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My point here is don't stress because

people are doing layoffs or 'cause they're

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hiring or they're not hiring, because

you never know how it's affecting other

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industries and how that company might

actually just do hiring in the next year.

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By the way, I used AI almost exclusively

to create this chart right here.

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Pretty cool, right?

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Well, you're kind of wrong because

this chart sucked to make with ai.

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At first, I asked it to go download

the historic stock data for ExxonMobil

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and Meta, and it said that it did

it and it created these charts.

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But I looked at the data and some

things looked a little bit too

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perfect and a little bit too linear,

and so I went and investigated on my

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own, and sure enough, it literally

just made up the stock price data.

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It didn't get even remotely close.

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And I was about to show thousands

of you false data created by ai.

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Then it still took me like three hours to

make this chart, which honestly, I think

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I could have made this entire thing in

three hours just using Python with no ai.

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And finally I got to the chart where

it was almost ready to show you guys

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like I wanted to clean some things up.

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For instance, I wanted to move the title

from Behind these filters right here.

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I wanted to remove my grid lines and

I wanted to create some captions here.

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I ran out of Claude Credits

to actually edit this graph.

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So all of this to say, I

don't think you're cooked.

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I don't think data jobs are dead, and I

don't think AI is going to replace you.

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I think the data job market

right now is about what it

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should be in a tight economy.

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So if you enjoyed this positive outlook,

do me a favor, hit like and hit subscribe

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because I have a lot more data content

I wanna share with you this year.

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