Both data engineers and data scientists work with data exploration and analysis. They are two of the most lucrative career choices in India today, with impressive salary slabs. For both these careers, you will need good big data skills, along with hands-on experience in programming languages like Java, Scala and Python. This will help you extract information and insights from business data.
The size of the data engineering market in India stood at $18.2 billion in 2022 and is expected to grow at a CAGR of 36.7% to reach $86.9 billion by 2027. The data science field is also growing at an unprecedented rate, with high demand in sectors like healthcare, gaming and e-commerce.
If you want to make the most of this opportunity, consider GeekLurn’s Data Science Architect Program, in partnership with NASSCOM and IBM. After the completion of this course, you will be eligible for the role of a data science engineer, data scientist, data architect and research analyst. It is a 24-month course with 6 months of live interactive classes and 18 months of sponsored project work at authorised research centres funded by IIM, ISB and IISC.
You can gain 1.5 years of real-time sponsored project experience certification as well. The course offers a 100% placement guarantee in collaboration with PAN India’s top HR Consulting Firms.
But before you enrol, here’s a comprehensive guide on data engineer vs data scientist.
Table of Contents
The role of a Data Scientist
Data scientists mine, clean and present data. Businesses also hire data scientists to manage, source and analyse large quantities of structured and unstructured data. Other responsibilities include building predictive models, data collection, presenting information with data visualisation techniques, proposing solutions and strategies to address business challenges, collaborating with product development and engineering teams and identifying valuable data sources.
You will need to be adept at data wrangling, cloud computing, database management, multivariate calculus and linear algebra, probability and statistics and deep learning. The soft skills required for this profession include critical thinking, adaptability, curiosity, communication and being a team player.
The role of a Data Engineer
Data engineers construct dataset procedures that help with data mining, modeling and production. Their responsibilities also include testing at periodic intervals to identify bugs. The main role of a data engineer is to design and build systems for storing, collecting and analysing data. They also create and maintain data architecture, conduct research, automate tasks and detect patterns for data aggregation. Data science engineers can ease tasks like accurately estimating metrics for fraud or customer retention. They can obtain data from different databases, including SQL, MySQL, Excel and Oracle DB.
Some of the basic skills you will need to succeed in this profession are coding, data architecture, data warehousing, Apache Hadoop-based analytics, skills to work with different types of applications like IoT, web, mobile and desktop, and advanced knowledge of programming languages like Python.
Difference between Data Engineers and Data Scientists
| Data Engineer | Data Scientist |
| Builds and maintains structures and systems to store, organise and acquire information that is relevant to businesses. | Analyses data to predict trends and extract insights. |
| Prepares data infrastructure for analysis and prepares the elements and raw data, like formats, scaling, resilience, managing, integrating and optimising data. | More focused on developing hypotheses using knowledge of statistics. |
| Builds free-flowing data pipelines and mixes a variety of big data technologies that can help in real-time analytics. | Conducts online experiments and works with machine learning algorithms. |
Which is a better career choice in 2022?
As of March 2022, data engineers are more in demand than data scientists. This is mainly because their work cannot be automated by tools. The average salary of a data engineer is also higher than that of a data scientist. So, it could be a good idea to consider taking up data engineering for a bright career path. You will be able to take advantage of roles like data architect, database developer and solutions architect. These help to refine your engineering skills and create a deeper knowledge of cloud computing and processing.
You should also have a detailed understanding of what is data science engineering before you sign up for a course. However, if you enjoy writing machine learning algorithms, performing statistical analysis and using creative ways to solve issues, being a data scientist could be your forte.
The bottom line:
A clear idea of data engineers vs data scientists, their roles and responsibilities and career scope in India can help you pick the right field. Just remember that data engineering is more about the nitty-gritties of data preparation while more sublime tasks are meant for a data scientist.
Neel Neeraj
Neel is a Product Manager with an interest in Data Science, Machine Learning, Cloud Computing, DevOps, and Blockchain with expertise in Python, R, Java, Power BI and Data analytics.
