Important things to know
Before we get into the article, it is important to provide basic definition of SQL and Python to guide your understanding.
What is SQL?
SQL stands for Structured Query Language. It is used to communicate with databases.
In most organisations, data is stored in databases. These databases could contain sales transactions, employee data, or any other type of business information.
SQL helps you query the data stored in the organization's databases. It retrieves, inserts, updates, and deletes data stored in databases. Data is a great asset to organizations, and the ability to ask questions and derive insights from data makes SQL a core skill to have for data engineering roles.
Common Uses of SQL
Data Analysis: SQL queries help analysts draw meaningful information from data sets.
Reporting: Businesses make use of SQL to generate regular reports, which can be used for business audit
Business Intelligence: It is the core of most BI tools like Tableau and Power BI, as they rely on data stored in a database
What is Python
Python is a high-level, general-purpose programming language known for its simple syntax and easy readability. Other than data engineering, Python is also used in data analysis, machine learning, and artificial intelligence.
It has a large ecosystem of extensive libraries, such as Pandas, Matplotlib, PySpark, and Apache Airflow, making it suitable for both beginners and experienced professionals.
Because of its wide adoption and broad application across other career paths, it continues to be one of the most widely used programming languages for data roles.
Common uses of Python
You need it to build and automate repetitive tasks across data pipelines
It can be extended using external libraries like pandas, Airflow, and PySpark, which let you scale your workflow
It creates opportunities for other careers. If you intend to explore other career paths, like data science or machine learning, knowledge of Python becomes very important.
Which one then should you focus on?
From our explanations above, we have helped you understand the roles of these tools as you embark on your learning journey as a data engineer to make you better informed on which tool to master, which helps increase your career visibility.
SQL and Python stand out as two core skills consistently mentioned in data engineering job descriptions. SQL helps data engineers work with data stored in databases. Python goes further by supporting analysis, data science, automation, and advanced workflows like machine learning and AI.
For a beginner who is starting their career in data engineering, one of the first questions you could ask is: Should I learn Python or SQL first?
This is a very common confusion that every beginner, who, without proper career guidance, is likely to face. You hear that Python is powerful and used actively in data engineering and now in AI. At the same time, you also hear that knowledge of SQL is important because it enables you to have access to data stored in a database.
Which one should you learn first?
For a data engineering beginner, the choice isn't SQL vs. Python; it is about learning them in the right job context. The choice sometimes depends on the job roles you are assigned to, rather than which language is ‘better’ or which one is easier to learn.
Learn SQL when you need to query and manipulate data stored in relational databases efficiently.
Learn Python when you require building and automating data pipelines or advanced data workflows.
Both tools complement each other and make you a more effective data engineer. Beyond theoretical learning of the tools and their functions, you must work on projects and apply them to real business problems to solve problems. This is why we do what we do with our work experience programs especially for African immigrantss in the UK, US & Canada who constantly need to show tech recruiters in their country that they have local experience. Our testimonials from previous participants may be all the inspiration that you need. Click here to watch some of them.
Whether you should learn SQL or Python depends on what you want to achieve and whether Python or SQL is more useful for the roles you are assigned to as a data engineer. Generally, SQL is important if you are directly involved with database querying and manipulation, while Python offers a wider range of choices, which enables you to build data pipelines and enable automation if you are building complex extract, transform and load (ETL) workflows.
Both skills are highly in demand by employers, hence having either of them will significantly increase your chances of getting employed and deepen your knowledge in data engineering. Professionals with both SQL and Python skills are better positioned for long-term career growth. Because you read this to the end, you have an opportunity to book a free clarity call with any of our Career Coaches at a time most convenient for you. They will be on standby to guide you through all that you need to get started with building your portfolio and increasing your chances of landing jobs. Click here to book.
