Big Data Engineering: Mapping Your Career Path in India

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Big Data Engineering: Mapping Your Career Path in India

Do you enjoy working with data and have an analytical mind? Then becoming a big data engineer might just be the perfect career path for you. In this article, we'll guide you through everything you need to know about how to become a big data engineer in India.

Understanding Big Data Engineering

Big data engineering is a field that involves the development and implementation of methods to process, store, and analyse large amounts of data. The ultimate goal of big data engineering is to create value from large volumes of structured or unstructured complex data. This involves designing systems that can efficiently handle high-speed data in real-time, integrating different types of datasets and sources, creating robust storage mechanisms, and building algorithms to analyse the resulting information.

Big data engineering differs from other related roles like data analyst or business intelligence analyst in that it focuses on processing extremely large datasets. These datasets are usually too large for traditional processing methods and require specialised tools to optimise performance.

Companies utilise big data engineering techniques to make informed decisions. For example, companies can use big data analysis to track consumer behaviour patterns, improve their products and services through customer feedback analysis, predict future trends in their respective industries, identify potential business opportunities by tracking market trends and much more.

Career Paths and Job Roles for Big Data Engineers

Different job roles in the big data engineering field

There are several job roles within big data engineering that young professionals can explore based on their interests and skill sets. Some popular job roles include:

1) Data Architect - responsible for designing efficient database systems that meet business requirements

2) Data Analyst - analyses large volumes of data to uncover insights and trends that can drive business decisions

3) Machine Learning Engineer - develops algorithms and models using machine learning techniques and tools to provide insights from data

4) Big Data Engineer - designs, builds, and maintains the infrastructure required for big data storage and processing

Big data engineering is relevant across many industries, including healthcare, finance, telecommunications, retail, e-commerce etc. All these industries require processing large datasets to make more informed decisions.

Skills required for different job roles

Different job roles within big data engineering require specific skill sets. For example:

1) A data architect requires knowledge in database design, ETL (Extract Transform Load), SQL/NoSQL databases etc.

2) A data analyst requires knowledge in statistical analysis, Machine learning algorithms (Clustering Regression etc.), Data visualisation tools like Tableau or PowerBI etc.

3) A machine learning engineer requires knowledge of programming languages such as Python or Java with expertise in machine learning techniques such as Decision Trees or Random Forests etc.

4) To become a successful big data engineer requires expertise in Hadoop's ecosystem and other technologies such as Apache Spark or NoSQL databases.

Benefits of upskilling bootcamps

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Benefit	Description
Short duration	Bootcamps usually last 3-6 months so you can quickly learn skills needed for a specific role
Hands-on experience	Bootcamps are designed for hands-on training exposure to real-life problems
Access to mentors	Bootcamps offer access to industry experts who can provide guidance throughout your career
Career networking opportunities	Connect with peers that can help expand your network

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Education and Certification Options for Big Data Engineers

While a degree is not compulsory to become a big data engineer, possessing one may provide an advantage when job hunting. A Bachelor's Degree in Computer Science or a related field is considered an entry-level requirement by some companies.

For those who want to achieve senior positions as managers or directors within the industry, pursuing higher education such as a Master's degree or Ph. Ds in computer science can be beneficial.

Another way to demonstrate your expertise as a big data engineer is through certification courses like Cloudera Certified Hadoop Developer (CCHD) or Hortonworks Certified Developer(HDPCD). These certifications validate your knowledge of specific tools used in Big Data Engineering.

Salary Range and Upward Mobility of Big Data Engineers in India

Big data engineers in India earn an average salary of INR 7.9 Lakhs per annum, with salaries ranging between INR 3.6 Lakhs - INR 20.1 Lakhs per annum depending on experience. Experience is a crucial factor that influences salary growth in this field.

If you are looking to advance your career as a big data engineer, acquiring specialised certifications, skills and experience can lead to upward mobility opportunities such as promotions or moving into higher-paying roles.

Upskilling Opportunities for Aspiring Big Data Engineers

Upskilling is essential to keep up with the ever-changing trends in the industry. Here are some upskilling opportunities for aspiring big data engineers:

Tableau Desktop Specialist Certification Training
Google Cloud Certified – Professional Data Engineer
IBM Certified Data Engineer – Big Data
Microsoft Certified: Azure Data Engineer Associate

These courses provide specialisations within different aspects of big data engineering helping individuals develop new skills.

Industry Growth and Trends in Big Data Engineering

The global market size for big data was valued at USD 138 billion in 2020 and is expected to grow at a compound annual growth rate (CAGR) of over 17% from 2021 to reach USD 229 billion by 2025. India, being home to several multinational companies in the field of technology and finance, has a huge potential for Big Data Engineering.

The future scope of Big Data Engineering in India looks promising with significant advancements in areas such as Artificial Intelligence and Machine Learning. The need for skilled professionals in this field is expected to grow over time, making it an excellent career opportunity for young professionals looking to expand their horizons in the technology industry.

Unlocking the Power of Big Data Engineering

Becoming a big data engineer in India is an exciting opportunity that offers many career options and earning potential. As you've learned, the core skills required include programming languages, databases, data visualization, machine learning, and cloud computing.

You can pursue educational degrees or certification courses to enhance your skills and knowledge. With a salary range of ₹3.6-20.1 lakhs per annum depending on experience, upward mobility opportunities are excellent. The future scope for big data engineering in India is vast in various industries like banking & finance, healthcare, e-commerce & retail, and more.

To unlock your potential as a big data engineer in India, explore financing options for career-focused upskilling/certification programmes at WIZR.

FAQs

1. Does big data require coding?

Yes, programming skills are essential for a successful career in big data engineering. However, the extent of coding varies depending on the job role.

2. Is Python mandatory for big data?

Python is one of the most popular programming languages used in big data engineering; however, expertise in other languages like Java or R is also valuable.

3. Is big data used in AI?

Yes, AI relies heavily on analysing large volumes of structured/unstructured complex data. Therefore, knowledge of big data engineering is beneficial when pursuing a career in AI.

4. Will AI replace big data engineers?

AI and big data engineering are complementary fields, and both require a different set of skills. Therefore, the need for skilled big data engineers is not likely to diminish anytime soon.

5. Which language is required for big data?

Languages like Python, Java, and SQL are necessary for building tools and applications in big data engineering.