Team Sep 03, 2024 No Comments
“Data engineer or data scientist? Who earns more? Which one is better?”
If you have these questions in mind, you are in the right place.
You see, data engineers build and maintain architectures required for data collection and storage, whereas data scientists analyze the data to find insights and help organizations make smart decisions.
In this post, I will discuss more about the differences between data engineers and data scientists.
You will know what they do, what skills they use, how much they earn, and what career opportunities they get. This will help you decide which career path you should choose.
Though data engineers and data scientists both work with data, there are many differences in their roles and responsibilities. Let’s understand that…
A data engineer basically designs, builds, and maintains the systems and infrastructure that collect, process, and store large datasets.
They create data pipelines, build ETL processes, and manage databases and data warehouses. All this is to make sure the data is clear, reliable, and accessible for analysis.
Data engineers work closely with data scientists, business analysts, and other stakeholders to understand the organization’s data requirements and fulfill them.
They use tools like Apache, Hadoop, Spark, Kafka, SQL, and NoSQL databases (e.g. MongoDB). Their work involves a lot of coding and includes programming languages like Python, SQL, Scala, and Java.
A data scientist simply analyzes data collected by data engineers and finds valuable insights that can solve business problems. They may use statistical methods, machine learning and AI algorithms, predictive models, etc., to solve specific business problems.
They also have to communicate their findings through visualizations like dashboards, charts, graphs, etc. The purpose is to help non-technical stakeholders identify trends and patterns in complex data and make smart decisions.
Data scientists use tools like Adv. Excel, Python, R, SQL, TensorFlow, PyTorch, scikit-learn, and data visualization tools like Tableau and Power BI. Their work is more about statistics, maths, analytical thinking, and problem-solving.
Since their work is different, it’s obvious they will have different sets of skills (although there may be some overlaps):
To be a successful data engineer, you need to learn these skills:
Ivy Professional School’s IIT-certified Cloud Data Engineering course not only helps you learn the above in-demand skills but also lets you work on industry projects to gain hands-on experience. This is a 45-week live online course where you learn to use tools like Azure, Hive, MongoDB, Spark, etc., from industry experts.
You also get mentored by IIT Guwahati professors and professionals in companies like Amazon, Google, Microsoft, etc. Besides, you will earn certifications from IIT Guwahati, IBM, and NASSCOM to boost your credibility as a data engineer.
And to understand what topics you must study to become a data engineer, you can go through the latest data engineering syllabus.
You need to gain the following skills to become a successful data scientist:
If you want to master the above skills, you can join Ivy Professional School’s IIT-certified Data Science and AI course. Again, it’s a 45-week live online course, so you can join from anywhere, engage with instructors, and solve your doubts instantly.
You will be trained by experts and exposed to real-world problems through 10+ projects, 40+ case studies, and 50+ assignments. Ivy also provides CV-building sessions as well as mock interview sessions to make you completely job-ready.
And to understand what topics you must study to become a data scientist, you can go through the latest data science syllabus.
Let’s look at the most asked question about this topic: “Do data scientists earn more than data engineers?” I will simply provide you the average numbers, but remember that the salary is highly influenced by factors like location, industry, company size, etc.
The average salary of a data engineer in India is ₹8,50,000 per year. That’s the base pay amount. If you consider the bonuses and commission, the average total pay for a data engineer becomes ₹9,50,000 per year.
The salary increases as you gain more experience. For instance, the salary of a senior data engineer with 2-4 years of experience can be anything between ₹11 lakhs to ₹24 lakhs per year. And if you are the lead data engineer with 5-7 years of experience, you can expect to earn ₹ 18 lakhs to ₹32 lakhs per year.
The average salary of data scientists in India is ₹12,00,000 per year (base pay). And again, if you consider the bonuses and commission, the average total pay of data scientists is ₹13,60,000 per year.
Senior data scientists with 2-4 years of experience can earn between ₹16 lakhs to ₹30 lakhs per year. Whereas lead data scientists with 5-7 years of experience can earn ₹22 lakhs to ₹38 lakhs per year. So, it’s clear that data scientists earn more than data engineers.
The world is generating more data than ever. In fact, we produce 402.74 million terabytes of data every day. This means businesses need skilled individuals to make sense of the massive amounts of data. And that’s why both data engineers and data scientists are in high demand.
Data engineering provides you amazing career opportunities. The global big data and data engineering services market is expected to be valued at USD 163.80 billion by 2030, growing at a CAGR of 15.48%.
This type of growth means there will be more demand for skilled data engineers in the coming years. And it’s already happening: the demand for data engineers with over six years of experience increased from 27% in 2023 to 38% in 2024.
You will find more and more opportunities in data warehouse engineering, ETL development, data pipeline architecture, big data engineering, and cloud data engineering roles. All these are focused on the technical aspects of data management, like data extraction, transformation, loading, data integration, and data quality.
Related: Is Data Engineering a Good Career?
Data science is one of the high-income skills that is in huge demand. You can open a job platform like GlassDoor or LinkedIn, and you will find over 10,000 data science jobs in India.
And the demand is going to explode in the coming days. This is evident from a report that predicts that the global data science market is expected to grow from $133.12 billion in 2024 to $776.86 billion by 2032.
Data science provides you many opportunities for growth and advancement. You can be a data analyst, business intelligence analyst, machine learning engineer, data storyteller, and so on. The rise of AI will open new applications like natural language processing, computer vision, predictive analytics, etc.
So, both data engineering and data science provide exciting opportunities to grow and succeed in your career. Now comes the most important question…
Related: 7 Reasons to Become a Data Scientist
There is no right answer to that. That’s because what may be better for others may not be a better choice for you. So, the real question is- what do you enjoy, and what kind of work excites you?
If you love coding, solving technical problems, and building systems, data engineering might be the better option for you. As a data engineer, you will design, build, and maintain architectures like data pipelines and databases to collect, store, and organize data.
On the other hand, if you love playing with numbers, analyzing data, and finding useful insights, data science could be a better choice for you. As a data scientist, you will basically study a problem from different angles, think analytically, develop solutions, communicate it to business stakeholders, and help businesses make smart decisions.
Whatever excites you the most is the right career option for you.
Prateek Agrawal is the founder and director of Ivy Professional School. He is ranked among the top 20 analytics and data science academicians in India. With over 16 years of experience in consulting and analytics, Prateek has advised more than 50 leading companies worldwide and taught over 7,000 students from top universities like IIT Kharagpur, IIM Kolkata, IIT Delhi, and others.
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