How to Become a Big Data Engineer?

In today's world, big data has become increasingly important in almost every sector, including business, healthcare, finance, government, and science. It refers to large, complex, and diverse sets of data that require advanced computational and analytical techniques to extract insights and value. Big data is characterised by the volume, velocity, variety, and veracity of the data.

A big data engineer is responsible for designing, building, and maintaining the infrastructure that enables the storage, processing, and analysis of large volumes of data. The role of a big data engineer is critical in enabling organisations to extract insights and value from big data.

To become a big data engineer, one may choose to pursue a Btech Degree in Data Science as foundational knowledge. Further, they can pursue a specialisation in a related field, such as computer science, statistics, or business data analytics.

What is Big Data? 

Big data is an extremely large and complex set of data that cannot be processed using traditional methods or tools. 

The data is typically generated from various sources, such as social media, sensors, and other digital devices, and comes in different formats, such as text, images, audio, and video.

It requires advanced computational and analytical techniques to extract insights and value and is used by organisations to inform decision-making, gain competitive advantage, and drive innovation.

What’s the role of a Big Data Engineer?

Some of the key responsibilities of a big data engineer include:

• Designing and implementing data pipelines: A big data engineer is responsible for designing and building data pipelines that can efficiently and reliably process large volumes of data. This involves selecting the appropriate technologies and frameworks for data ingestion, storage, and processing.
• Building and maintaining data storage systems: Big data engineers design and build data storage systems capable of handling massive amounts of data. This includes deciding on data storage technologies like Hadoop Distributed File System (HDFS), NoSQL databases, and cloud-based storage solutions.
• Developing data processing applications: They are also responsible for developing and deploying data processing applications that can analyse large volumes of data. This involves developing applications that can handle batch processing as well as real-time processing.
• Ensuring data security and compliance: To ensure that the data storage and processing systems the engineers have built are secure and compliant with relevant regulations such as GDPR, HIPAA, and PCI-DSS is also their key responsibility. 
• Collaborating with data scientists and analysts: Big data engineers work closely with data scientists and analysts to understand their data processing and analysis requirements and develop solutions that meet those requirements.

Now, You must be wondering how to become a big data engineer in India. Let’s delve deeper and find this out. 

How to become a big data engineer in India? 

To become a big data engineer in India, here are some steps you can follow:

1. Obtain a Btech Degree in data science or in computer science, information technology, or any other related field. This will provide you with a solid foundation in programming, algorithms, data structures, and computer systems.
2. Once you have gained experience in data processing technologies such as Hadoop, Spark, and NoSQL databases, you can become a professional in this particular field. 
3. Develop programming skills in languages such as Java, Python, and Scala, which are commonly used in big data processing.
4. Gaining experience in cloud computing platforms such as AWS, Google Cloud, and Microsoft Azure, which is used to deploy and manage big data applications, can also be rewarding for you.
5. One should develop skills in data visualisation and analytics tools such as Tableau and Power BI, which are used to analyse and big data.
6. Participate in online communities and forums related to big data to network with other professionals and stay up-to-date with the latest trends and technologies.
7. Pursuing certifications in big data technologies such as Cloudera Certified Developer for Apache Hadoop (CCDH) or Hortonworks Certified Apache Hadoop Developer (HCAHD) can help you demonstrate your expertise to potential employers.
8. Apply for internships or entry-level positions in companies that work with big data technologies. This will provide you with hands-on experience and help you gain the skills necessary to become a big data engineer.
9. Continuously learn and improve your skills through online courses, workshops, and conferences to stay competitive in the fast-changing field of big data engineering.

By following these steps, you can become a big data engineer in India and build a rewarding career in one of the most in-demand fields in the technology industry.

Top Recruiters for Big Data Engineers

Some of the top recruiters for Big Data Engineers are

1. Amazon
2. Google
3. Microsoft
4. IBM
5. Facebook
6. LinkedIn
7. Twitter
8. Airbnb
9. Uber
10. Netflix

All these companies have a massive amount of data to process and analyze and they are always on the lookout for Big Data Engineers to work on their data processing and analytics platforms.

Skills Required to Become a Big Data Engineer

To become a successful Big Data Engineer, you need to have a combination of technical and soft skills. Here are some essential skills required to become a Big Data Engineer:

• Strong Programming Skills

You should have expertise in programming languages such as Python, Java, Scala, etc. to build robust data processing pipelines and work with data processing frameworks such as Hadoop, Spark, and Flink.

• Data Modeling and Database Management

You should have a deep understanding of data modelling concepts and database management systems such as SQL and NoSQL databases.

• Understanding of Big Data Technologies

You should be familiar with distributed computing systems and big data technologies like Hadoop, Spark, and Flink.

• Knowledge of Data Warehousing

You should have design and implementation experience with data warehouses and data marts.

• Knowledge of Data Visualization

To create meaningful reports and dashboards, you should be familiar with data visualisation tools and techniques.

• Problem-Solving Skills

You should be able to analyse complex data problems and create effective solutions.

• Communication Skills

To collaborate with other team members, business stakeholders, and data scientists, you must have excellent communication skills.

• Project Management Skills

You should have project management experience and be able to work independently or as part of a team.

• Analytics and Machine Learning

To extract insights from large datasets, you should have experience with analytics and machine learning techniques.

• Continuous Learning

You should be eager to learn new technologies and keep up with the latest trends in big data engineering.

Admission Process for B.Tech Degree in India

Before moving further, let's check out the admission process for B.Tech in India:

• Educational Qualification: Candidates should have completed their 10+2 or equivalent examination with Physics, Chemistry, and Mathematics as compulsory subjects. Some colleges may also require candidates to have studied English as a compulsory subject.
• Minimum Marks: Candidates should have obtained a minimum aggregate of 50% marks in their 10+2 examination. Some colleges may also have a higher percentage requirement.
• Entrance Examination: Candidates should have appeared for a national-level or state-level engineering entrance examination such as JEE Main, JEE Advanced, BITSAT, MHT CET, or others, depending on the college.
• Age Limit: Candidates should be between 17 and 25 years of age at the time of admission. However, the age limit may vary depending on the college and category of the candidate.
• Domicile Requirements: Some states may have domicile requirements for admission to B.Tech programs in government and private colleges. Candidates should check the domicile requirements of the state in which they are seeking admission.

Top Colleges offering B.Tech Degrees in India

Here’s the list of the Top 15 B.Tech Colleges in India-

Name of the College	NIRF Ranking	Average Fees	Average Salary
Indian Institute of Technology (IIT), Madras	1st	₹ 5.31 -10 Lakhs (Total Fees)	13.5 LPA
Indian Institute of Technology (IIT), Delhi	2nd	₹ 8-9 Lakhs (Total Fees)	20 LPA
Indian Institute of Technology (IIT), Bombay	3rd	₹ 8-9 Lakhs (Total Fees)	23.26 LPA
Jadavpur University, Kolkata	4th	₹ 9,600 -1.21 Lakhs (Total Fees)	10 LPA
Indian Institute of Technology (IIT), Kanpur	5th	₹ 8.76 Lakhs (Total Fees)	20 LPA
Indian Institute of Technology (IIT), Kharagpur	6th	₹ 8.5 Lakhs (Total Fees)	27 LPA
Indian Institute of Technology (IIT), Roorkee	7th	₹ 11-12 Lakhs (Total Fees)	16.80 LPA
Vellore Institute of Technology (VIT), Vellore	18th	₹ 1,95,000/- per annum	8.19 LPA
National Institute of Technology (NIT), Tiruchirappalli	21st	₹ 6-7 Lakhs (Total Fees)	10.8 LPA
National Institute of Technology (NIT), Surathkal	22nd	₹ 6-7 Lakhs (Total Fees)	23.03 LPA
Birla Institute of Technology and Science (BITS), Pilani	29th	₹ 4.84 -19.94 Lakhs (Total Fees)	30.37 LPA
College of Engineering, Pune (COEP)	52nd	₹ 2 Lakhs (Total Fees)	6 LPA
Indian Institute of Information Technology (IIIT), Hyderabad	54th	₹ 3,00,000/- per annum	32 LPA
Manipal Institute of Technology (MIT), Manipal	55th	₹ 18.52 Lakhs (Total Fees)	10.36 LPA
Delhi Technological University (DTU), Delhi	63rd	₹ 9,31,400/- (Total Fees)	13.24 LPA

Salary Stats for Big Data Engineers in India 

According to various sources, the average salary for Big Data Engineers in India is around INR 10-20 lakhs per annum (approximately USD 13,500 to USD 27,000) based on the experience level and seniority of the engineer. However, the actual salary may vary depending on several factors such as experience, location, industry, and company size.

The table below shows the Big Data Engineer salary in some of India's top recruiting firms. Examine these companies based on your preferences and apply right away.

Company Name	Average Annual Salary
Tata Consultancy Services	₹ 6,01,672 per year
Cognizant Technology Solutions	₹ 8,02,678 per year
Knowledge Lens	₹ 6,94,151 per year
IBM	₹ 11,80,000 per year
Infosys	₹ 6,12,556 per year
Accenture	₹ 8,63,199 per year
Exadatum	₹ 7,51,151 per year
Fractal	₹ 9,13,836 per year
Jio	₹ 7,00,000 per year
Wipro	₹ 6,05,823 per year
Capgemini	₹ 7,43,438 per year

Source- Glassdoor 

It is worth noting that Big Data Engineers with advanced skills and certifications may command higher salaries.

Common Interview Questions for Big Data Engineer Jobs 

Here are some common interview questions for Big Data Engineer jobs:

1. What are some of the biggest challenges you've faced while working on big data projects? How did you overcome them?
2. What is your experience with distributed systems and data processing frameworks like Hadoop, Spark, and Flink?
3. Can you explain how you would design and implement a data pipeline that can handle large volumes of data and ensure data integrity?
4. What is big data analytics and why is it important? 
5. Have you worked with any NoSQL databases like Cassandra or MongoDB? What are the advantages and disadvantages of using NoSQL databases for big data projects?

Conclusion 

Overall, Big Data Engineering is a highly demanding field with a growing scope all over the world. To excel in this field of technology one must have advanced knowledge of programming and other essential skills. Having hands-on experience in the latest tools and techniques can be highly beneficial for a student pursuing B.Tech Degree. If you also seek expert knowledge and advanced hands-on experience in various project works, Sunstone can be the best choice for you. 

FAQ- Big Data Engineer 

How many years does it take to become a big data engineer?

The time it takes to become a Big Data Engineer can vary depending on educational background, work experience, and career goals. On average, it can take 4-5 years to get a job as a big data engineer. 

Is it hard to be a big data engineer?

Being a Big Data Engineer can be challenging due to the complex and rapidly evolving nature of big data technologies. However, with the right skills and training, it is a rewarding and in-demand career path.