I would recommend both Python and R. I wouldn't say SQL is the most important skill for a data scientist. It is one of the most important components when it comes to storing data. Also, nowadays most data scientists are interested in Big Data, for which SQL is becoming obsolete. Perhaps you should look at NoSQL databases such as Neo4j, ArangoDB, etc. instead. In terms of analysis, you should check out Machine Learning and Deep Learning techniques. A number of articles can be found online. I suggest that you first choose a field of interest and then browse the resources accordingly. Providing articles without knowing your personal interests is very difficult, however, the following links may be useful. Thanks
I am not a data scientist, but am a retired technology professional. In my experience, programming languages come and go, but mathematics is constant. I believe a firm grasp of statistical concepts will help you over the long run more than a programming language du jour. That said, however, you will obviously need to be able to manipulate data, especially big data as Jagajjit Sahu points out. And for that you will need to be moderately proficient in a language. Good luck in your chosen path.
I think knowing python or any of the R languages will be enough. Both can do many tasks in the future, from data visualization to building neural networks. If your learning Sql is necessary for your planned career, it will be easy to learn. But I think a data scientist should know enough statistics, mathematics and even linear algebra apart from these languages .
In general, it depends on project or company you work with. Python or R, both of them are good to have skill on it. If you more focus on company, try to study Python. For academicians, usually R is preferred.
For the second question, It is not totally true, but in my opinion, that is the basic thing data scientist know about SQL. So, you have to know it. And I suggest to study NoSQL as well since in recent years, many data scientists work with NoSQL
Given the versatility of the Python language, I will recommend it to new beginners in data science. Also, SQL will come in handy as you develop in your career. You should also consider taking courses in statistics and machine learning for predictive analytics. Finally, visualization tools such as Tableau and PowerBI will be helpful for creating dashboards to share your insights from data analysis.