Jagpreet
21 June, 2024
Table of Contents
Hey Siri!
How do you know the answers to all our questions?
If you ask Siri how she knows the answers to all your questions, she might give a response similar to this:
“I use a combination of your device’s information, data from Apple’s servers, and information from the internet to provide you with answers. I’m designed to help you find what you need quickly and easily.”
How do technologies like Siri by Apple, Bixby by Samsung, and Alexa by Amazon address our questions and provide us with the necessary answers? Each technology and artificial intelligence tool is constructed with a special algorithm that imitates human intelligence and decision-making abilities. These technologies require data that combines information from various sources, such as the Internet, the server of the company it belongs to, and your personal information that you allow it to access.
In a nutshell, data is the core of each technological invention. Data has become necessary for professionals in fields like data science, data analysis, and many others. It is the source from which we make our decisions. Today, businesses cannot fathom functioning without the appropriate data concerning their consumers and the market. They must be constantly aware of their customers’ changing trends, popular choices, and preferences. Data is a non-negotiable for any industry today. It is the past we saw, the present we live and the future we imagine.
Data, however, is stored in massive servers, infrastructure, and systems. It demands meticulous management and proficiency. A data engineer is a qualified professional who manages this large amount of data. Data is processed using tools specially designed to fit the purpose. However, a lot of big data cannot be processed using simple or traditional tools. It requires more efficiency. This is where a big data engineer ensures this data is put to judicial use.
Big data is a large amount of data or data sets that need efficient handling and analysis to optimise it to its maximum potential. A Big Data Engineer is a qualified professional who develops, maintains, evaluates, and tests a company’s data. Businesses across all industries must work with massive amounts of data. They need this data to make more informed decisions and guide their business operations. Data is integral to their work in this industry and areas such as science, governance, and pharmaceutical industries. Data is, therefore, collected in a large amount. It is segregated and stored systematically for convenient access.
It must be used correctly to make this data useful to the company or business. This can further help improve the organisation’s efficiency, profitability and scalability. Big data engineers come into the picture when this data must be managed by systematically arranging them into systems where it can be accessed and maintained. If you think this is similar to the work of a data scientist, then it is not! A data scientist is primarily responsible for analysing the clean data used to generate insights using several methodologies for the company’s future.
Here are the roles and responsibilities a Big Data Engineer has to fulfil:
Organisation: Creating systems that collect, store and process the data systematically.
Research: Constantly researching and updating the data systems to extract the appropriate value from them while improving their quality.
Programming: Learning and using programming languages and tools that help develop solutions for the data.
Collaboration: Working closely with data analysts, data scientists, and other team members.
Collection: Conduct research and get all the required data together in one place to improve the efficiency of a business’s decisions.
ETL: An ETL process stands for
Extract: Extract data from different sources such as databases, files or the internet.
Transform: Clean and format the data gathered.
Load: Load the data that has been transformed into the appropriate storage systems.
All these listed colleges are accredited by NAAC:
Course | Fee |
Amity University Online | INR 6,250 per month |
BITS Pilani | INR 1,22,200 per semester |
Symbiosis Skills and Professional University | INR 2,10,000 |
Vishwakarma University | INR 1,92,945 per year |
Here are the job profiles of a big data engineer, their descriptions, and the salaries offered. The salary figures can vary depending on the job profile, recruiter, qualifications, educational background, experience, and skills.
Job Profile | Salary |
Data Scientist | ₹14,05,000 to ₹18,00,000 per year |
Data Analyst | ₹6,32,000 to ₹8,00,000 per year |
Database Administrator | ₹8,50,000 to ₹10,00,000 per year |
Machine Learning Engineer | ₹17,50,000 ₹25,00,000 per year |
Business Intelligence (BI) Developer | ₹6,50,000 to ₹6,95,000 per year |
Big Data Engineer | ₹8,00,000 to ₹10,00,000 per year |
Recruiter | Paying Scale – Approx. |
Netflix | INR 9,00,000 to INR 11,00,000 |
Oracle | INR 10,00,000 to INR 21,00,000 |
Walmart | INR 16,00,000 to INR 27,00,000 |
Microsoft | INR 10,00,000 to INR 26,00,000 |
INR 10,00,000 to INR 21,00,000 | |
INR 7,00,000 to INR 10,00,000 |
Source: Glassdoor
Data engineering is a demanding job. Not just in the present but even in the future. This job profile demands skills like precision, artificial intelligence, machine learning, and programming languages. All these skills and field knowledge significantly contribute to the job position. The profession of data engineering also requires a considerable investment of time, education, and work experience. Therefore, along with your education, you can also take up some online courses, internship experiences or a job that can help you better understand this profession. Once you begin applying the principles of data engineering in real-life work projects, you will be able to understand better what it is like to implement what you learn in theory. For such degrees, your experience matters more than the theoretical knowledge you learn. Therefore, you must take up such projects and enhance your skills.
All the best!
You can begin by obtaining a Bachelor’s and a Master’s Degree in the fields closely related to big data engineering. These fields include computer science, business data analytics or statistics. Along with this, you must also know coding, statistics and data handling.
The academic background and work experience this profession requires can make it a little daunting and overwhelming. However, the return on investment this profession offers can be impressive if you know how to channel your efforts correctly.
Scala and Python are two of the most demanding programming languages this profession requires.
Yes, this profession is demanding in various industries and businesses.
Here are the skills:
Machine Learning and AI
NoSQL
Data Pipelines
Hyper Automation
Programming