What I'd Do As a Junior Candidate in Mid-2026. Freestyle Fridays (June 26, 2026)

Hey, what's up? It's Joe. Welcome to Freestyle Friday for June 26th. So this morning I did a fireside chat, a Q&A with a company.

Sometimes I'll do this depending if I'm asked nicely to do it. In this case, I was. So I think it's a good opportunity to kind of get to understand other people's worlds. They can get to understand mine.

And in this case, it was interesting. One of the questions that really stood out to me is something I'm actually asked a lot. I get messages from people, emails, you know, get asked at conferences, this question here, and it's more pertaining to juniors, but I think the advice could also be extended to people who are a bit more experienced. But the question is, you know, what do I do?

Right? I'm a junior, I studied data, maybe this data engineering, maybe it's analytics, data science, so forth. But, you know, in a lot of cases, it feels like the rug has been pulled out from underneath junior candidates, they maybe went to school or boot camps learning one thing. Now, the world is expecting something different from them.

And, you know, I really want to unpack this, because I think it needs to be addressed. I can't say that I have maybe all the answers here, but at least I have my answer on how I would approach this. But yeah, being a father of two boys, the question does come up often, both myself and from them, just what to do, what to prepare for, and so forth. So here's some advice.

If you're getting started in your career, or if you're starting over in your career, or if you're experienced and having questions, I think some of this, again, applies. But I think the main thing is that AI is here. I don't think it's up for debate whether you should be using it, learning it, whatever. If your school has not been equipping you with AI skills, it's on you to learn these things.

From what I understand, some schools are a bit more forward-thinking with AI. Some have pretty much rejected it. That's not under your control, unfortunately. That's the school's decision and the professor's decision and so forth.

So you're going to have to deal with what's in front of you, right? And that's just the world we're in. You know, so I would definitely say, you know, don't just be, don't prompt, you know, your AIs. Learn to build systems with them, right?

You know, use AI to, you know, say, augment the things that you learned in school, right? you probably learned. I'm just going to say like core data skills, at least tactically, would be things like SQL, Python databases. Maybe you learn data modeling, maybe not.

Data cleaning, basic APIs, Git, Linux and so forth, right? Maybe some cloud fundamentals. I think some colleges are doing cloud certifications as well. But these haven't gone away, obviously.

But I would say that, you know, from what I can tell, employers are looking for, it's really it's not just you know do you you know chat gpt right that's it's pretty much table stakes everyone uses that but it's more about how you can leverage ai to do the things that you've learned right so this means maybe using ai to debug code maybe generate tests write documentation rapidly prototype you know designs you know whether it's architectures or data pipelines or so forth, summarizing aggregating data sets as well.

I do think that you still need to understand the underlying mechanisms in which you'd query data using SQL. I know how to debug SQL. I still think this is a skill you need, but AI is increasingly going to be doing most of this work for you. But this means you need to understand where AI is wrong, right?

You need to be able to review AI generated code with a critical eye. and so you know i would say that it's uh you know so these are kind of the table station just in terms of leveraging ai to do the things you've learned right and as far as i can tell from employers like this is still sort of what they're looking for obviously if you can take it to maybe so i could instead of that kind of level one really which is using ai to augment maybe your existing knowledge um you know and experience and then granted that as a junior you probably don't have much experience with it kind of is what it is.

But before I get into what I consider level two, let's do an ad from our sponsor Revify. So Revify has been a long time sponsor of the show and the newsletter. And they have something actually really, really cool. They just announced just launched their AI DBA.

So AI database administrator. And if you know the team at Revify, they're responsible for building some of the fastest, most badass databases in the world. Their CEO, Sanjay, is one of the sharpest people who understands query optimization in the world. And so when I see them coming out with an AI DBA, this means better pay attention, right?

So in this, you know, so far it's proving to be a big success, right? So, you know, five-minute zero-touch setup. You can reduce your cloud costs by, you know, 30 to 70 percent. 24 to 7 autonomous tuning.

And it insane right So one orchestrator three platforms 18 specialized sub agents So if you So if you have a need to control your cloud costs I pretty sure that like everybody You want to continuously manage FinOps, observability, quality, performance, and governance across your cloud data estate. Check out Revify. Go to Revify.com slash AI-DBA.

Again, that's Revify.com slash AI-DBA and check it out. And thanks to Revify for sponsoring the show. So what I would consider to be sort of level two really is, you know, the people who can start building workflows with AI and agents.

Right. And so, you know, but as a junior, right, you probably I'm pretty sure your school hasn't given you a project in terms of building AI workflows. that they have, that's awesome, by the way. But what I find increasingly valuable in terms of these skills is doing things like MCP, model context protocol, basically just being able to connect your AI to different data sources, Querium, RAG is still very popular.

You should learn that. Have a basic familiarity with vector databases. And what's interesting now is you know formerly i would say unsexy topics like governance quality and knowledge right so we're talking semantics ontologies graphs these are becoming very very popular uh this is quote the of context according to some pundits and so forth but you know the the thinking is real where we have all this unstructured data out there and we need to make sense of it we need to um you know bring bring unstructured data and tacit knowledge and all these places into to one spot.

And so, you know, if I were to say a new skill you should learn, um, you know, dive into semantics, um, knowledge and, uh, you know, the associated technologies and, and the underlying, um, you know, kind of first principles of these things. Right. Uh, so I would say this is an area where, uh, you know, even for established people, this scenario I'd be diving into a lot. Uh, that's one of the things I talked about today in this, um, you know, fireside chat was really just how the worlds of knowledge and data or, or, you know, some converging really.

And so being just a quote data person, I don't think it's enough anymore. And so, you know, as a junior candidate, right, this is sort of one of these things where, you know, it's a lot to ask, right? You barely know data and now you're being expected to learn knowledge. And so this is where I think AI can really help accelerate your learning and also, you know, your visibility, right?

Which we'll get into in a bit. But, you know, the thing that's going to help you stand out, too, is just having a portfolio of projects. Right. This has always been the case.

But right now, you know, you can use AI to really help build interesting portfolios that you can demonstrate a working knowledge of various things. So some things come to mind is like traditionally build a data pipeline or analytics project in DuckDB and have that in GitHub. Totally do that. But take it a step further.

Come up with an AI-assisted data pipeline. Show the workflow you're using with loop engineering and harnesses and all this other stuff, which you'll have to learn about, obviously. But AI can help accelerate your learning in this area, too. And so I would say keep building.

build cool stuff and show it off right um i think github's great uh the problem with github is you can obviously like vibe code a bunch of slop and throw it on there and call it your own and you know people may not be any um wiser to it uh make videos about this or write about it in blogs as well right now i'd say if you're going to write and it's something i had to chastise um you know some people this week for doing but if you're going to write to make sure you're not just copy pasting the first thing that comes out of like chat gpt right i've been getting article submissions for my practical data community newsletter.

And it's very obvious people just copy paste it from ChatGPT. And the thing is, if you're going to do that when trying to show off your portfolio, right, it doesn't, it's not a good look. So, you know, I'd say like just make it your own, but demonstrate that you can communicate what you've built as well. This helps establish, you know, actually this is in my Discord group today.

somebody was asking how to learn how to give interviews with candidates, right? How to conduct the interview. And it's one of those things where nobody can really prepare you for it. I think you just have to kind of go in and do it.

But the thing you really need to demonstrate as a person being interviewed is competence and communication, right? So if you're going to build something, You should be able to describe how it works. You should be able to understand what it does and how it works. And again, communicate that.

Because all too often, especially right now, it's super easy for somebody just to, you know, again, fire up their chat to BOT, like make a bunch of slop or, you know, a cursor or whatever. Put that on GitHub, call it their own, not understand a single line of code that's there. But that's besides the point. But, you know, it looks impressive.

but that's why you got to be able to justify what you're doing because people will dig into um you know so your rationale behind what you build so you know but it as i dig into some of these numbers right you know it old numbers that I looking at here But, you know, maybe half of data analytics job postings mention AI. I'm sure it's a bit more now. This is kind of late 2025. But, you know, when I hire people as well, the things I'm looking for are not just your technical skills, your tactical chops.

That's great. But what I, when I, if I were to look at a junior candidate, things I'm looking for are the things that I can build upon as I teach you. Right. So the things I really look for is like curiosity.

Right. If you're curious about the world, this probably means you're willing to learn about it and dig into things. Right. So you have to be able to learn quickly.

That's another thing. You have to be able to learn well. Right. Learning quick and forgetting things doesn't really help you.

Right. I want to make sure that you come into this using that sense of curiosity to also learn about the business and the domains that you'll be operating in. I think that's super important. Being able to communicate with the people within those domains and business operations and understanding their world, I think, is key.

So being able to communicate and demonstrating a level of critical thinking. so especially right now uh with ai i think critical thinking is going to be well not going to be it is worth a lot more you need to be able to discern what's good what's not what works what doesn't what's correct what's wrong right but you need to know and be able to judge and critically think about things not just blindly accept whatever the ai tells you to build not just blindly accept whatever your boss tells you to build too i know you're junior but you You should be able to, you know, be able to take a request and sort of parse it.

And maybe in the back of your head, say, this is cool, right? Or maybe here's some things that we need to work on. So, you know, so these are some of the things I would say that I would consider when I'm a junior candidate, right? I know the job market is quite brutal right now from what I hear.

But again, the things you need to really level up on are just, you know, obviously the core things you learned in school. That kind of goes without saying you spent the time, you spent the money to be there. Hopefully you learned something, but then apply AI to, um, you know, sort of leverage, uh, those learnings, right. And leverage yourself, uh, portfolio projects, demonstrate what you've learned, be able to communicate it.

And then again, the five traits really that, um, you know, I, I, uh, considered be almost more important than the tech skills is really just being curious, learning continuously and quickly. understanding the business, getting in, understanding the people, the domains, talking with them, communicating with them, and then finally being able to think critically. Now, on top of this, the other thing I would suggest is you have to put yourself out there. As I've written extensively about, it doesn't seem to matter whether you're a junior candidate or an older candidate.

The people I see who are successful in general are the ones who have taken the time to build their network, get out there, meet people, put yourself in front of opportunities, right? If you show up time and time again, you know, consistently, don't just show up once and expect things to happen for you. It doesn't work that way. But if you show up, you know, contribute to communities, help build things, go, you know, volunteer at events and meetups and communities and so forth.

But over time, you know, more senior people will recognize that and see your level of enthusiasm as being something, you know, they might, you know, want to pay attention to. It might, you know, if they have a position, maybe, you know, they might take a shot at you. I know I've hired people like that, you know, and the thing is networks are sort of a long game. I'll give you an example.

Yesterday I was at my climbing gym and ran into an old friend of mine. I've worked with him, geez, I don't know, a long time. Yeah, maybe 15, 20 years, something like that. But, you know, this person lamented that he just got laid off, right, from a job at some company.

When I talked to him, it didn't seem like he was going anywhere. And then he mentioned that he, you know, he's kind of bummed. He got laid off. But at the same time, he's pretty happy because, you know, it's just kind of a weird fit anyway.

And, you know, he asked if I knew of anything out there because, you know, the job hunt was pretty hard. And, in fact, I did, right? And so earlier that morning, I was talking to another friend of mine who had messaged me about an opportunity in a local area. And it just so happens that, you know, my friend who got laid off, his skill set matched, I think, quite well with what this other person's looking for and the person they want to hire.

Like, very, very close. And so I made a match with the two, linked them up, and we'll see where it goes, right? No guarantee it'll work out, but I think that that at least demonstrates the power of networking, right? In this case, I'm sort of sitting in the middle of this, but it's, you know, I have a very big network for sure.

But, you know, that obviously benefits, you know, my friend, you know, both sides really benefited from this, right? And that, you know, the other person who had the job opening, I know that person almost 10 years, right? From a past thing I worked on, right? So the thing is when you make these relationships with people you never know what going to happen down the road It could be 10 years or more Right But the thing is the data world in the industry is very very small It seems big but you know given enough time, you become senior and that world gets smaller.

Right. People kind of filter out of the industry for one reason or another. You know, and it's just, you know, the people who are left, I suppose we, you know, we all know each other. Um, and you know, I think to a large extent, we all have each other's backs too.

And so I think that's the other thing we're just, you know, take the time to build relationships, but be genuine about it. Right. But you know, especially right now, if you're trying to shotgun a bunch of resumes out, um, you know, hoping to get a job that way, it's going to be very, very difficult. Right.

So it's the opportunities I've always, um, found either for myself or for other people were really the result of taking the time to build relationships, cultivate them, and not expecting anything in return, right? If you're trying to approach it that way, being transactional, you're doing it wrong. People can see through it. You're doing yourself a giant disservice.

Just be a person, get to know other people. And over time, right? You build your network and you never know what's going to happen. But yeah, that's the other piece of it, right?

So you have the tech part, which I talked about earlier, all the skills you're going to need there. And then this is the other part, right? The network, you know, and just building the relationships. And I think if you can do those two things and stay on top of your skills, you know, continue building your network and I think paying it forward in a lot of cases, volunteering, you know, doing things that don't make any sense because you're not getting paid for it.

Hey, guess what? You're a junior, right? The reality is you're going to be, you know, beating the pavement pretty hard. You're going to be, you know, just shoveling shit, as they say.

And that's just, it's called paying your dues, you know. I know it's hard for some people to imagine this world where you have to actually put in the work to get something out and probably not see it in return for a bit. But hey, you did that in school already, right? You spent four years, maybe in college, maybe more if you did your master's or whatever, or maybe some boot camp.

But it's like you paid money. You worked your ass off, right? With no guarantee of a job in return. And that's just how it is, right?

Like I spent years, decades building a network, not expecting anything in return, putting out content, not expecting anything in return, you know, building things, working at companies, you know, and it's just like, this is just life is how it is. right so if you're junior again i know it's tough but you know um there are you know you're going through a major technological inflection point so i'm sure the people who are you know trying to hire you too they have the same questions about you know what's what's their viability what's their um you know it's what's their future and so forth so everyone's kind of in the same boat but the thing you can control is what you can control that's your skills that's how you bring yourself to every day that's how you bring yourself um to others and to the world and that's really the things you can control.

And I think if you can control those and just bring, you know, yourself and your best version of yourself every day, you know, you definitely have a chance, a better chance than most, right? So anyway, that's my advice for juniors and data as of June 2026. But again, as a question, I get a lot, a lot, a lot, like I would say several meshes, you know, in various places a week, just what should I do, right? I get a lot of meshes, from seniors as well and very similar types of questions.

But again, I want to address this more to juniors because I think it's just, it would be hard to be a junior today for sure. I think it's because there's so much perceivably stacked against you. But then if you kind of, again, peel back the curtain a bit, you realize, you know, at the end of the day, a hiring manager is going to want to hire somebody who is going to be a good investment, right? and the thing is ai's equalize the playing field in a lot of respects where you know seniors and and above like they're they're all scrambling too to figure out this world right so everyone's kind of back at the same starting line in a lot of ways so i would say that if you think you have a disadvantage maybe you do maybe you don't but the cool thing is you don't have any bad habits to break um and that's that's a it's a it's a big advantage in some sense right um but but anyway right but you know the bar has been raised for sure in terms of what constitutes a junior getting hired these days because, um, you know, AI is just that much more capable, which means you need to, um, you know, sort of become one with the AI, right?

But at the same time, don't lose yourself, you know, read a lot, learn a lot outside of AI, right? It's not the end all be all. Um, but yeah, good luck. Good luck to you.

And, um, you know, on that note, I'm going to get back to the book, just, um, uh, doing all the final finalization stuff. Now artworks proved to be a bit tricky um i want to do these hand drawings i really like the idea um but then there's other books coming out on my new label which i'll be announcing soon and you know so i need to come up with a standardized um image uh formatting for those and so forth so anyway that's what i've been struggling with lately but uh manuscripts good to go you'll be seeing updates on subsec um very very soon um but yeah so it's my that's going to be my day plus reviewing uh one of my other author's books right because he's uh he's getting close to finishing his too.

So the fun never stops just reading, writing, and all that fun stuff. But anyway, I hope you have a great weekend. And yeah, take care. Bye.