As someone in the data/coding industry, I say yes... but it depends on two important factors:
1. What type of job you're looking for
It's not easy to become a Data Scientist just by knowing Python and SQL, but those are definitely two of the most important skills you'll need. However, most data scientists start off as an analyst (business intelligence analyst, data analyst, etc) OR as a developer (software dev, hard-core python development, etc).
If you're looking for a job "querying SQL databases" (as you referred to it), that sounds more like a Database administrator (DBA) or a web developer who needs to pull data into a website. Those jobs probably won't care that you know Python. The DBA job will require a nice amount of IT background, and the web developer job obviously needs HTML/CSS & a whole lot more probably. If either of those two jobs are what you're looking for, then my answer to you is no, you don't really have what you need just with SQL and Python.
However, Data scientists, data analysts, & data engineers spend a lot more time manipulating and transporting the data. So yes, data manipulation is usually SQL, and Python is a bit skill to have too, so you're certainly on the right track if that's the job of job you're hoping for.
The other important part is:
2. If you're willing to take an entry level position.
Like I mentioned, most data scientists start off in a lower-level data position. If you have SQL and Python skills, and can somehow prove that you actually have those skills (such as with projects that you can show or talk about), then it's likely you can find a company who will take the risk of hiring you. A math background definitely helps in that case - I'd recommend making sure to state that clearly in your resume.
In my experience, I've found the business intelligence (BI) has the lowest entry barrier for people new to the data industry. It's mainly because BI professionals don't have to know SQL - I know many excellent BI folks who focus on the functional side (building charts, helping people define KPIs, etc - the business side of BI but they wouldn't build anything in SQL unless their life depended on it. Happens most often in the consulting world.) The other reason for the lower barrier in BI is that many of the tools are meant for people who aren't super technical, so they can use drag-and-drop interfaces or "Excel-like" tools, rather than dealing with heavy data modeling or pure data querying functionality.
But the point is that you have to start somewhere. Ideally go straight for the gold and see if you can land a job doing really cool data stuff, but my personal opinion is: It's more likely that you'll be able to start off as a technical data analyst working in a business intelligence tool. (Which is definitely a good job, don't get me wrong! It's just fairly different than data science.)
Yes, you're in a good place to move forward with your career goals. There is A LOT more to learn to become a data scientist, but most of it has to be learned on the job by dealing with very large data and just by getting real-world experience. That's just how it goes.
The only other thing I'd suggest learning is a BI tool like Domo (great for getting more experience with MySQL) or Treasure Data (great for getting more experience with Python). Tableau, PowerBI, and others are good too if you want to enter the BI field, but those tools more focused on the visual side & have less SQL/manipulation functionality.
You're definitely in a good spot to get started, though!