They very well might when it's outside the core remit of the company. Companies do this all the time - outsource/subcontract work so they can focus on what they're good at.
Yes, they might be able to build software that works for (relatively) close to free now. But that still has marginal cost in terms of extra resource to build it. Then it needs to be maintained, upgraded to meet changing internal requirements, it needs to be secure, they need to be able to trust it does what it's supposed to.
Sure, the cost of all of that has come down, but it's still a lot of work when they could just entrust another company to do that for a cost they're willing to pay. And companies are often happy to pay a lot in B2B contracts.
Just to reinforce this: look at the cost savings from cloud-exits - yet companies still readily build out in the cloud. FOSS has existed for decades, yet companies still pay for proprietary alternatives. Build vs buy exists on more dimensions than just cost alone.
The bright side is that analytics engineer is a relatively modern job title, previously it was largely bundled in with data engineer, and before that, data scientist. So you're either already relatively early in your professional career or have adapted between programming disciplines once already.
I also (personally! I'm in data engineering for my part) feel it's one of the safer roles from an AI perspective. Yes, you'll be writing a lot less code in the future, but that's never been the particularly difficult part of your job: SQL is dead easy to use.
The difficult part is picking up all the business context and knowledge in order to work out the best ways of representing complicated and messy data for the business. AI can help to some degrees there, but if you're great at your job, your judgement is going to be built on so much business context that both can't be written down and would be too vast to feed into the model.
Sure, AI can do some of the job, but you'll always thrash it in terms of quality (whilst getting to spend less time doing the busywork of just writing your thousandth predicate of the day!). And worst comes to worst, all the business knowledge you have in your head makes moving into analytics a far more viable lateral move.
And that one is definitely AI proof. If all companies use AI for their analytics, they're going to be moving largely in lockstep with each other. Humans might be far worse, but often far better, so I'd be willing to bet that through sheer randomness that over time companies using human analytics will outperform those relying on AI.
Yes, they might be able to build software that works for (relatively) close to free now. But that still has marginal cost in terms of extra resource to build it. Then it needs to be maintained, upgraded to meet changing internal requirements, it needs to be secure, they need to be able to trust it does what it's supposed to.
Sure, the cost of all of that has come down, but it's still a lot of work when they could just entrust another company to do that for a cost they're willing to pay. And companies are often happy to pay a lot in B2B contracts.
Just to reinforce this: look at the cost savings from cloud-exits - yet companies still readily build out in the cloud. FOSS has existed for decades, yet companies still pay for proprietary alternatives. Build vs buy exists on more dimensions than just cost alone.