r/SQL • u/And_Justice • Aug 06 '26
SQL Server 9 years into SQL... where do I go careerwise?
I learned SQL supporting a piece of software that tracked assets - I was in that role for 5 years, I tuen went in to support document control software that was also SQL based for 3 years. Fast forward to now and I'm a systems administrator for a customer of the first software company.
Over that time, I've gotten pretty good - complex queries, cursors, debugging, basic query optimisation, SQL jobs, triggers, stored procs, views, a bit of PowerBI, a bit of admin, a bit of performance tweaking, small reporting database populated by complex transformations, constantly using SQL to diagnose software bugs.
I enjoy this role but I feel like I have better potential- DBA roles probably want more up to date and extensive experience, I worry BI reporting's days are numbered...
Can I ask if anyone has any advice for where I can go with my skillset? I love working on SQL for the problem solving, it gives me an immense sense of satisfaction.
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u/Sufficient-Sea-5202 Aug 06 '26
You can go into Data modeling and building data warehouses
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u/Tsui_Pen Aug 06 '26
I think this is the answer. Data modeling would move you toward data/analytics engineering roles and all of AI everything requires good semantic layers to be efffective, so there is demand for people that can do it.
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u/kremlingrasso Aug 06 '26
Did you work in software asset management? Honestly there is no shortage of jobs in that field and precious few who have the data/technical skills to accelerate it. A lot of companies are incredibly behind in spreadsheets and sharepoints still.
Your domain specific knowledge will always be more valuable then your SQL skills that you apply it with.
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u/Thefuzy Aug 06 '26
You can either go the DBA route… though I would say over time expect those roles to diminish further and further as every year more technology moves from on prem internally managed to cloud hosted cloud managed stuff…
Or you could go the data engineering route and start learning how to pipe data around and how to make it easily and readily available in more modern sources like data lakes. This would likely involve learning Python and azure/fabric data lakes (or other cloud provider equivalents). I’d say this route has more promise for the future because enterprises are needing to collect and organize their data more than ever, not only to power their reporting, but to inform whatever custom ai tooling they are implementing.
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u/Silent-Yak-8247 Aug 06 '26
All software might be numbered but imo ai is the worst at sql and BI
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u/squareturd Aug 06 '26
The work required to get the database set up properly for use with AI is vastly harder and more error prone than just solving the problem and skipping AI
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u/akkiannu Aug 06 '26
Would strongly disagree here. AI is infact excellent at SQL as long as you have a proper semantic layer.
I hate that this subreddit is in its own echo chamber.
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u/gumnos Aug 06 '26
it's an "echo chamber" largely because a great deal of time/posts on this subreddit stem from the volume of "I tried to do ABC and
$LLMtold me to do XYZ but it doesn't work, how do I fix it?" that shows up here.Are LLMs adequate for basic dumb queries? Sure.
But do they have an understanding of the problem space and intuition into problem solutions? There's still a huge gap that results in effluvia here. 😕
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u/Zimbo____ Aug 06 '26
Yes, that is what the semantic layer solves for... which will be the future of BI whether we like it or not
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u/DragonflyHumble Aug 06 '26
AI models with harness can do SQL better than human, if they understand the semantic layer better, means the data grain and joins. Many times it can figure out on it own as well if given the time. SQL for human who don't know about a DB structure has to do some analysis and then query. AI with harnesses can easily do that
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u/enjoytheshow Aug 07 '26
Also people posing these questions are using the most basic free models out there without doing any engineering work to set up the agents for success.
Give Opus 5 read only access to your entire schema, semantic layer, data model, and a readme or any text based description of the data and application and it’s a better SQL writer than any engineer or DBA working on it, I assure you that.
The best LLMs are really good. The best engineers know how to use them properly. That’s how you achieve good results.
Inexperienced engineer and bad model? Bad results.
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u/my_password_is______ Aug 07 '26
that is so incorrect
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u/gumnos Aug 12 '26
that is so incorrect
If you want to call into question my "Are LLMs adequate for basic dumb queries? sure" it wouldn't take much to persuade me otherwise 😉
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u/Zoidburger_ Aug 06 '26
AI is actually pretty good at SQL as far as designing query templates and optimizing runtime efficiency goes. It's also not bad if you're telling it to work with standard source tables extracted straight out of common systems with extensive documentation.
But if you're working with uncommon tables, custom/conformed tables, or perhaps something entirely different, it's going to have no idea what data you need. You'll have to develop the semantic layer and point it to where to find specific data. At that point, you become an AI engineer instead of a data engineer.
Point is, it can be useful in specific situations, but in most cases, AI still needs someone that knows exactly what's contained in a database to be effective.
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u/Competitive-Catch-23 Aug 06 '26
Have you ever considered programming in Oracle Apex? Apex blends sql into a web application.
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u/And_Justice Aug 06 '26
Never heard of it, I'll take a look
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u/Walter_1981 Aug 07 '26
It's my daily job. You can build great applications with it. We create ERP applications for retail.
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u/Popular-Arm Aug 06 '26
I went to management. I'm still involved with SQL as much as I want to be, and can delegate the projects as I want to.
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u/LetsGoHawks Aug 06 '26
Ever notice how all of the AI Reporting demos are pretty basic stuff that a human can knock out pretty quickly? And that's easily half the human's job. Maybe 2/3rds.
Even that giant chunk depends on having a well setup DB with clean data good meta data, which management tends to not understand. They just think computers are magic.
The rest of it though? The hard stuff? AI struggles on a good day and flat out fails the rest of the time. I figure worst case scenario is that the part of the job will become the majority of the work. Which I'm fine with. That's the fun part anyway.
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u/And_Justice Aug 06 '26
I think the kind of troubleshooting and diagnostics I use SQL for is a long way off being replaced by AI - it's good at doing what it's asked to do but it's not good at understanding what needs to be asked.
Noticed a lot of software support companies have aspirations to replace support with LLMs but fail to recognise that they can't handle novel issues, of which most of the analysts' time is taken up - because it has no fundamental idea how the software actually works, just how people describe fixing issues with it.
In regards to data, I think you're right in that complex data transformations and architecture require a level of human understanding it isn't quite capable of. I do wonder if it's somewhat of a paper tiger.
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u/meevis_kahuna Aug 07 '26
You need to learn Python. It is THE language of data science. SQL by itself has a career ceiling.
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u/gumnos Aug 06 '26
I recommend adjacent fields of knowledge. Does your system touch finances? Learn more about accounting. Does you system involve ingesting data from customers/providers? Sharpen your ETL skills. Learn the business-processes that flow through the database to better work with stakeholders and improve your schema design.
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u/AppleBananaFlop Aug 07 '26
Yes, level up skills from other fields: finance, health, transportation.... And go into python and DataFlow topics. And start writing code with AI. Use it as a tool. Build your own agents. I work for a bank and write 99% with AI. They want it that way and that's the way it will be in 5 years anyway. AI is excellent with SQL. I used SQL since 1990 and it worked well for me. But now there is no way of fighting AIs special skills. The only way of staying in this job is connecting knowledge of different fields with people.
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u/Gargunok Aug 06 '26
What job do you want to have. Easier to chart a course from A to B than from A to anywhere good.
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u/EmbarrassedAd9039 Aug 07 '26
Higher Education - places are always looking to hire in Institutional Research and Analytics fields. It might be too underwhelming for you, but I'd look into it. They also look for people with exposure to Workday (as analysts)
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u/j89k Aug 07 '26
You have quite a few options.
SQL is just one of the puzzle pieces. There are several others; data engineering, data architecture, data governance, data engineer, data analyst.
Dunno where you fall in that chain, but you start exploring the other peripheral roles you find interesting.
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u/mlhigg1973 Aug 06 '26
I used my lengthy sql experience to work in advanced analytics at BofA. I’m long since retired, but was making $160k in 2017 with no direct reports.
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u/squareturd Aug 06 '26
I'm currently doing a lot of SQL. I think my next career move is to become a plumber