The field of data engineering is becoming increasingly popular. It is the fastest-growing tech job that is highly in demand and offers good earning potential. The data engineers play a critical role in building infrastructures that empower AI systems. It means that as technology is getting advanced, job openings for this role will increase more in the future.
If you want to become a data engineer but are wondering where to get started, worry not. All you need is some essential skills and in-depth tech knowledge. To help you out in this journey, here is a step-by-step guide to becoming a data engineer in 2025.
Step 1: Learn the Fundamentals
Begin by grasping the basics of data engineering. You should focus on learning data warehousing, data modeling, and ETL (Extract, Transform, Load) processes. Once you get equipped with these core concepts, you will be able to prepare different datasets for analysis. Eventually, with a solid foundation of skills and experience, you can begin applying for data science roles at major global companies such as Intuit.
In case you are facing challenges in your educational journey, consider seeking help from various online resources. A wealth of material is available online about the fundamentals of data engineering.
Step 2: Master Programming Languages
As a data engineer, you have to communicate with machines. And it is not possible without learning programming languages, as an AI model cannot understand your language. That’s why you must take some time to develop proficiency in Python for data manipulation and automation.
However, when it comes to managing large databases and querying data, you must know SQL (Structured Query Language). Otherwise, you would not be able to create, manage, and maintain databases for different systems.
Step 3: Understand Database Systems
Once you are done learning fundamentals and mastering programming languages, the next step is to understand database systems. You should gain expertise in both relational and non-relational databases. It is important to store and manage various types of data.
Step 4: Learn Big Data Technologies
To become a successful data engineer, you must familiarize yourself with big data frameworks, such as Apache Hadoop and Apache Spark. In this way, you will be able to learn the concepts of distributed storage and processing of large datasets.
Step 5: Explore Cloud Platforms
Cloud computing is becoming popular because of its unmatched features and security. This technology can accommodate the potential needs of various businesses, facilitating them in the best possible way.
You must get hands-on with leading cloud providers, such as Amazon Web Services (AWS), Google Cloud, and Azure. Focus on the services like S3 for storage and data warehousing.
Step 6: Develop Data Pipeline Skills
Learning and maintaining data pipelines is essential for a data engineer. For this, you can utilize tools such as Apache Airflow. It will help you schedule and manage complex workflows more efficiently and effectively.
Step 7: Build a Project Portfolio
After learning all the skills mentioned above, you are now ready to start your professional journey. To secure a job, build a strong portfolio and showcase your best academic and personal projects within it. Additionally, highlight your skills, such as creating a real-time data pipeline.
