How to Become a Data Engineer in 45 Weeks

Data engineers are the professionals who build the systems and infrastructure that help organizations collect, store, and analyze data. 

Since data-driven decision-making has become a necessity, the demand for data engineers has been growing rapidly. After all, the power of data helps companies gain more customers and boost revenue.

So, if you are a skilled data engineer, you can expect an amazing career with endless opportunities to learn and grow. In this post, we will discuss more about what data engineers do, how much they earn, and how to become a data engineer.

What Exactly Data Engineers Do?

Data engineers are like architects of the data world. They build systems that collect data smoothly from its source, like websites, apps, or sensors, and store it in places like databases and data warehouses. 

It’s the data engineers who help data scientists and analysts to easily access the data they need. So, they have to make sure that the data is accurate, consistent, and reliable for analysis.

They also have to ensure that systems can handle massive amounts of data and grow as the business grows. And they have to make this process efficient by optimizing the systems for speed and performance.

Various industries like technology, finance, healthcare, and e-commerce rely on skilled data engineers to build and maintain their data infrastructure. Here are some specific tasks that data engineers perform:

• Build scalable data pipelines to collect, process, and store data from various sources.
• Handle ETL (Extract, Transform, Load) processes to clean and transform data for analysis.
• Design and manage databases and data warehouses.
• Create data models that define how data is stored, accessed, and managed.
• Work with data scientists, analysts, and stakeholders to understand data requirements.
• Increase efficiency, improve security, and troubleshoot to maintain high performance.

Now, let’s take a look at why data engineering is such a great career.

What’s the Salary of Data Engineers?

The high demand and the specialized skills of data engineers translate into competitive salaries. For instance, data engineers in India earn an average salary of ₹8,62,000 per year. 

But that’s just the average figure. Factors like years of experience, location, and company size affect the salary. For example, Glassdoor reports senior data engineers with 2-4 years of experience earn salaries between ₹ 12 lakhs to ₹ 25 lakhs per year. Whereas lead data engineers with 5-7 years of experience earn salaries between ₹ 18 lakhs to ₹ 32 lakhs per year.

Similarly, the average annual salary of data engineers in Bangalore is ₹11 lakhs, whereas in Gurgaon, it is 11.9 lakhs, and in Mumbai, it is ₹9.6 lakhs. Larger companies with a heavy reliance on data (like tech, finance, and e-commerce) often pay more than smaller companies or those in less data-centric sectors.

If you are considering a career in data engineering, it’s a good idea to research the salary trends in your specific location and industry. Now that we know the perks of being a data engineer let’s understand how to become one.

How to Become a Data Engineer?

Here are 6 essential steps to becoming a cloud data engineer:

1. Get a Relevant Degree

Although it’s not necessary, if you have a bachelor’s degree in computer science, engineering, math, or a business-related field, it can really help. It will give you a strong foundation and help you understand the basics of programming, databases, algorithms, etc.

But if you don’t have a formal degree, you can join certification courses. This is, in fact, a great way to launch your data career. Courses not only help you learn industry-relevant skills but also help you gain hands-on experience, stay updated with industry trends, and be a credible data engineer. 

And if you join top-rated courses, like Ivy Professional School’s IIT-certified data engineering course, you will be mentored by IIT professors, receive career guidance, and get lifetime placement support.

2. Learn Technical Skills

A data engineer needs a set of technical skills to do their tasks effectively. Here are some of them:

• Programming languages like Python, SQL, Java, Scala, and R.
• Design and implement ETL pipelines.
• Design, build, and manage data warehouses.
• Big data technologies such as Hadoop, Spark, and Kafka.
• Design and implement data models to organize and structure data.
• Relational databases like MySQL and NoSQL databases like MongoDB.
• Cloud services include AWS, Google Cloud Platform, and Microsoft Azure.

Read this post to learn about the latest data engineering syllabus. However, try to stay updated with new trends and technologies. Things change fast, so you must keep learning new skills even after you become a skilled data engineer. 

3. Polish Your Soft Skills

Now, just technical skills aren’t enough to become a data engineer. You also need to sharpen your soft skills to do your job effectively. Here are some of the essential ones:

• Problem-Solving: You should be good at thinking critically to come up with innovative solutions. You also need analytical skills to troubleshoot and resolve data-related issues.
• Communication: You have to work with data scientists, analysts, and business stakeholders. You will need the ability to explain technical ideas clearly to people who might not be technical.
• Collaboration: You should have the ability to work effectively with others to achieve common goals.
• Attention to Detail: You should be careful and precise to ensure data is accurate and reliable for analysis.
• Project Management: You should know how to manage multiple tasks and projects efficiently.

4. Build a Solid Portfolio

A good portfolio is a powerful tool that can help you land your dream job. It basically shows the projects you have worked on and how you have applied your skills to solve real problems.

The portfolio helps you show some of your unique work and stand out from other job applicants. Since employers get a direct example of what you can do, you become trustable.

Here are some tips to build your portfolio:

• Choose a few key projects that clearly show your data engineering expertise. 
• Clearly describe what you did, the technologies you used, and the results you achieved.
• List the tools, programming languages, and technologies you used in each project. 
• Use graphs, charts, and diagrams to make your projects more clear.
• Write Medium posts to explain the problems you solved, your approach, and the outcomes.
• Keep your portfolio updated with your latest projects.
• Get feedback from your mentors and peers to improve your portfolio.

The key to building a solid portfolio is practicing good projects. That’s why Ivy Pro School helps learners work on industry and capstone projects in the data engineering course with E&ICT Academy, IIT Guwahati. It not only helps in the portfolio, but learners also gain practical experience and confidence to solve real business problems.