Team May 15, 2024 No Comments
Data engineers collect, organize, and store raw data. This helps companies uncover valuable insights, improve their products, and better target their marketing. That’s why companies value data engineers.
But is data engineering a good career? Are data engineers in high demand?
There’s actually a high demand for skilled data engineers, and the job offers a competitive salary and good learning opportunities.
If you see the numbers, the global big data and data engineering market is projected to grow from USD 51.7 billion in 2022 to USD 140.80 billion in 2028. So, you can also expect good job security.
Keep reading to find out more. We will explore what data engineers do, why this career path is worth pursuing, and what the future of data engineering is. So, here we go…
Data engineers are the plumbers of the data world, building pipelines that collect data. They extract raw data from different sources and store it in a usable format.
Data engineering is all about making data available, consistent, secure, and recoverable for an organization. For this, they have to build and maintain infrastructures like databases, big data repositories, and data pipelines.
Here’s a breakdown of their key tasks:
As a data engineer, you will often collaborate with data analysts and scientists to ensure data matches their needs and the organization achieves its goals. And that’s how you will be playing a critical role in helping businesses make data-driven decisions.
Here are some key data engineering skills:
SQL: You need to learn SQL queries and operations like data cleaning, aggregation, and error handling, as well as advanced SQL features like subqueries and user-defined functions.
Python: Python programming is essential. You need to learn Python basics, advanced data structures, functions for data preprocessing, data wrangling, debugging, etc. Besides Python, you can also learn programming languages like Java, R, and Scala.
Data Warehouses: A data warehouse is a data management system that stores large amounts of data from various sources in an organized way. You need to know how to design, build, and manage it so that businesses can carry out their BI, analytics, and reporting smoothly.
ETL Pipelines: ETL stands for Extract, Transform, and Load. It helps businesses collect, store, and use data efficiently. This involves taking raw data from various sources, cleaning it up, and then loading it into a single system for further use.
Big Data Processing: This helps you work with large amounts of data. You need to learn the fundamentals of big data and key technologies such as Hadoop, Apache Hive, and Apache Spark. You can work on projects that involve building and managing real-time data pipelines.
AWS, Google Cloud, Microsoft Azure: Cloud services are used to store and manage data over the internet, so you don’t need physical servers. AWS, Google Cloud, and Azure are technologies that allow you to do this. Simply gaining an in-depth understanding of Microsoft Azure and its application in data engineering would be enough.
Read this post to know more about the latest data engineering syllabus and skills.
You also need to develop certain soft skills to work smoothly in the corporate world.
The most important is communication skills, which are necessary to clearly explain technical details to non-technical colleagues and stakeholders. Good communication also helps you better understand the problems of your clients and get relevant feedback to deliver the best work.
You also need attention to detail, problem-solving skills, presentation skills, and the ability to work well in a team.
And obviously, to get a job, you need to know how to perform well in interviews. That’s why we at Ivy Professional School help our students by letting them participate in mock interviews.
So, now you understand that data engineers build the foundation for data-driven decision-making for organizations and what skills they need to do it. But does that mean it’s a good career path for you?
Well, let’s see some of the reasons why data engineering is an attractive career path:
High Demand: Businesses have to deal with massive amounts of data. This creates a constant need for skilled data engineers to collect and manage it. That’s why, in April 2024, there were over 10,500 job openings for data engineers across all industries on online job portals in India.
Impressive Salaries: With high demand comes high pay. Data engineers typically earn competitive salaries because of the value they bring to organizations. The average base pay of data engineers in India is ₹9,41,500 per year. And senior data engineers with 2-4 years of experience have an annual average base pay of ₹18,50,000.
Learning Opportunity: Data engineering requires creativity and problem-solving. You will constantly be challenged to design new data pipelines, clean up raw data, and find innovative ways to make data usable. This means you will get to learn a lot of tech and soft skills.
Creating Impact: You will work on a variety of projects across different industries, making a real impact on how businesses operate and make decisions.
Job Security: According to IDC, the global datasphere is projected to reach a staggering 175 zettabytes by 2025. This ever-increasing data volume creates a constant demand for skilled data engineers. That’s why data engineer jobs are expected to grow at a rate of 21% from 2018-2028 in the US. This means you can have a stable and rewarding career.
The above points make data engineering an irresistible career path. However, there are also certain challenges that you must take care of. Here they are:
Now, you will be able to judge if data engineering is for you or not. Let’s move on to the next section for an even better understanding…
First of all, it’s important to consider if this career aligns with your interests and skills.
If you like programming, are passionate about data, and love challenges, then the benefits of data engineering can outweigh the challenges.
However, you will need a learning attitude. The market is ever-changing, so a love for continuous learning is essential to stay relevant in this field.
You will also need communication and teamwork skills. Because data engineers often work with data scientists, analysts, and other professionals to help an organization achieve its goals.
If you match the above requirements, data engineering will be a rewarding career path for you that will offer good pay, job security, and the chance to make a real impact in the world.
The world of data is constantly growing. And you, as a data engineer, will continue to play a vital role in shaping its future. Here are some exciting trends to look forward to:
With the ever-growing importance of data, data engineers will be even more crucial for businesses of all sizes. If you are looking for a promising career, you can definitely consider data engineering.
If you want to learn data engineering, you can join Ivy’s Cloud Data Engineering Certification course.
This is an online course made in partnership with E&ICT Academy IIT Guwahati. So, you will be coached by IIT Guwahati professors as well as experts from Amazon, Google, Microsoft, etc.
The course will help you learn current industry skills, complete 30+ real-life projects, and become job-ready in just 45 weeks.
And this program is perfect for both college graduates as well as working professionals who want to upskill. Visit this page to learn more about Ivy’s Cloud Data Engineering course.
Is data engineering a good career in India?
Yes, data engineering is a promising career in India. With impressive salaries, job security, and a lot of learning opportunities, data engineering can help you achieve your career goals. And since the global big data and data engineering market is expected to grow from $51.7 billion in 2022 to $140.80 billion in 2028, you can expect the demand for data engineers will only grow with time.
Are data engineers in high demand?
Since data-driven decision-making has become a necessity, data engineers are in high demand. Companies across various industries need them to build and maintain the infrastructure needed for data collection, storage, processing, and analysis. That’s evident from the fact that data engineering jobs are expected to increase at a rate of 21% from 2018-2028 in the US.
Does data engineering involve a lot of coding?
Yes, data engineering involves a lot of coding. Data engineers use programming languages like Python, SQL, Scala, and Java to build data pipelines, manage databases, and make sure data is processed efficiently. If you want to be a skilled data engineer, you have to master the above programming languages, which you can easily do by taking online data engineering certification courses.
Do data engineers make good money?
The average salary for a data engineer in India is ₹8,53,500 per year. Location, industry, company size, and years of experience are some factors that can influence the salary. For instance, data engineers in Bangalore earn an average annual salary of ₹11 lakhs, and in Pune, it is ₹9 lakhs. But whatever the case, as the demand for data engineers continues to rise, salaries are expected to remain high.
Who gets paid more: software engineers or data engineers?
Both software engineers and data engineers are well-paid, but their salaries can vary based on factors like company, location, experience, etc. If you compare the average annual salary, data engineers earn ₹8,53,500, and software engineers earn ₹8,21,152, according to Glassdoor. So, data engineers can earn slightly more due to their specialized skills and the growing necessity of data-driven decision-making.
Is data engineering a stressful job?
The right answer depends on you and the company you will work at. However, like most technical jobs, data engineering can be challenging at times, especially when dealing with complex data systems or tight deadlines. The thing is, you have to ensure that data systems are efficient, reliable, and secure. Which can be stressful. But if you have mastered the skills, have good experience in solving data-related problems, and love programming, the work can be very rewarding.
Will AI replace data engineers?
Okay, that’s a hot question. AI can automate repetitive and laborious tasks like data ETL, data integration, data pipeline creation, etc. But it won’t fully replace data engineers. Skilled data engineers will be needed to perform those complex tasks requiring human expertise and creativity. So, keep improving your skills, stay updated with the industry, and learn to utilize AI. AI is your co-pilot, which can boost your efficiency and problem-solving ability.
Eeshani Agrawal holds an MS in Civil Engineering from Texas A&M University (USA) and has over 16 years of experience in data visualization, storytelling, and analytics. She has consulted for top engineering, manufacturing, and consulting firms worldwide and has coached over 9,000 professionals and students from leading institutions like IITs, IIMs, and ISI.
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