Big Data – the name indicates voluminous data, which can be both structured and unstructured. Many companies collect, curate, and store data, but how do they access the data in an instant? How do the analysts and other professionals identify the data they need? How do companies manage to handle the ferocious velocity at which data is churned? They then need to analyze the data, and hence, data architecture and analytics has gained prominence.
The methodologies involved in how Big Data is accessed and used for business intelligence can play a crucial role in surviving in a highly competitive environment.
What is Big Data?
Big Data is a minimum of 1024 terabytes of data. Companies use computational processes to manage the data, which is defined by volume, velocity, variety, veracity, visualization, and value.
Who is a Big Data Architect?
A Big Data Architect is like a traditional architect who visualize, design, and build structures. The only difference is that they build physical structures, while Big Data Architects deal with voluminous data sets that are growing by millions of data bytes. It is their job to integrate the large volume of data into an organization’s current system and create safeguards to protect the priceless data while ensuring it is easily and quickly accessible.
Big Data Architect Salary in India
Business decisions are often dependent on the trends the Big Data Analysts and Data Scientists are able to unearth from the large data sets. As companies have started shifting to big data to better understand and implement new business ideas, many new openings have raised for Big Data Architects.
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The Demand for Big Data Architect
Big Data has become a buzzword for nearly every industry. It can be reflected by the number of job opportunities you can have for this role. A simple LinkedIn search can land you on more than 5000 related job roles.
On Naukri.com, you can find more than 14000 results for Big Data Architect, which shows the rising demand for experts.
There is a requirement for Big Data Architect in almost every business. Telecommunication, Marketing, Healthcare, Retail, Government, Insurance, Banking, Finance – Big Data is fast becoming the lifeline of business decisions. So, the demand is high, but what is the salary that you can expect?
The Average Salary of a Big Data Architect
According to Glassdoor, the average salary for a Data Architect in India is above Rs 17, 00,000 per annum.
The average salary is impressive on its own. In comparison, the average salary in India for a software developer, which is the job that most Computer Science graduates choose, is around only Rs 5, 00,000.
This means that you could be earning three times more than your software developer counterparts if you have the right skills and are willing to put in that extra effort!
Factors Affecting Big Data Architect Salary in India
The three main factors affecting the Big Data Architect Salary in India are:
- Company – The bigger the data, the higher is the salary you can expect. It does make sense that the bigger the company, the more voluminous their data will be, and hence, you will get a higher salary.
- Experience – Your experience to build data management systems and operate them for optimum benefits will have an impact on the salary you get. Business decisions are based on the data, and hence, many companies will pay higher salaries to the right individuals.
- Location – The location of the company you approach for a Big Data role will have a direct impact on your final salary. Do remember that the cost of living in some of these cities is also higher in comparison to other cities.
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Big Data Salary in India: Based on Company
The company that you work for will have a direct impact on your salary. The image below shows the salaries that different companies in India offer, and as you can see that Tata Consultancy Services lead the pack with the average salary averaging at Rs 15,00,000 lakhs per annum. It is followed by Ford Motor Company, Wipro, and Deloitte. The requirement for qualified Architects is across industry types!
The role of a data architect can be very challenging, requiring skills that deliver results efficiently. This is why companies are ready to pay fantastic salary packages to candidates with the right experience and skillsets.
Big Data Salary in India: Based on Experience
Your earnings will largely depend on the experience you have in the industry. So, to earn a higher salary, you need more experience. According to PayScale, early in your career with 1-4 years of experience, you can earn a total compensation of more than Rs 8, 00,000 per annum. The salary can almost double to Rs 15, 00,000 per annum as soon as your experience with 5-9 years of experience. After the 10-year mark, you can expect to get paid over Rs 20, 00,000 per annum.
The image below captures the differences of a Big Data Architect Salary in India based on experience.
Thus, if you have the right skill sets and are willing to keep pace with the technological advancements through your careers, you can achieve the highest possible salaries on offer.
Big Data Salary in India: Based on Location
The salary also depends on the location. You can earn a higher salary if you are working in IT hubs like Bangalore, Hyderabad, and Pune. The hubs provide companies the right infrastructure to survive, and hence, you can find some of the biggest names in these locations. As the image below shows, Big Data Architect Salary in Bangalore, the IT city of India, is 17% higher than the national average. On the other hand, in Noida, a suburb of Delhi, the salary is 19% below the national average.
You can get almost Rs 22,00,000 per annum working in Bangalore, while the figure for Hyderabad is around Rs 17, 00,000 per annum.
So, you see, a few key factors affect the salary, but one thing is certain – you cannot perform the job without the right skill sets. Big Data is attracting some of the best talents from the tech field, and if you want to succeed, then honing your skills is essential. Freshers need to understand the job requirements while experienced personnel should keep abreast of the technological advancements in the field.
Learn more: Big Data Salaries Guide
Skills required by a Big Data Architects
You may want to earn an excellent salary as a Big Data Architect, but to do that, you need to develop the right skill sets.
- Knowledge about data architectures and an ability to handle and analyze large scale data
- You should be able to benchmark systems, analyze and identify any possible bottlenecks in the architecture, and then propose appropriate and efficient solutions to solve them
- The ability to process and analyze data to understand the behavior of the customer
- Have good knowledge about a scripting language like Python, Ruby or R. Language proficiency in C# and .Net are often required
- Good working ability and understanding of Hadoop to solve various problems
The job of a Big Data Architect is a highly technical one, but being a professional, some other skills are often expected by the companies.
- Excellent verbal and communication skills
- Ability to explain your work in plain language
- Be able to work in teams and in a fast-paced agile environment
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What does a Big Data Architect do?
The Big Data field has a plethora of opportunities, and so it is important to know what is expected.
Roles and Responsibilities
The role of a Big Data Architect is important as it aims to address big data problems and requirements.
- Assessing the structure and behavior of a certain problem, form feasible solutions and delivering the solutions using technologies like Hadoop
- Forming the necessary link between the organization’s needs and the Data Scientists and Analysts
- Responsible for developing as well as maintaining a full life cycle of a Hadoop solution
- Designing the technical architecture for a possible solution based on the analysis and selected platform
- Designing the application architecture and are responsible for a smooth development process, including testing and deployment
The architect needs to be skilled and specific for this cross-industry, cross-functional and cross-domain job. As various other important tasks may depend upon the output given by a data architect, companies often tend to pay quite handsomely for this role.
Expectations and requirements by employers
For a task as heavy as this, companies often have a certain level of expectation and requirements. Some of these are:
- A bachelor’s degree in Computer Science, Information Technology, or other related streams.
- For mid-management and senior management, experience in the field is a must
- Good understanding of information systems and their applications to data management processes
- Ability to perform a detailed analysis of business problems and use the technical environments to formulate a feasible and efficient solution
- Experience working with SQL and NoSQL databases, including Postgres and Cassandra.
- Excellent Hadoop skills, along with data mining and modeling tools
Check out: Hadoop Developer Salary in India
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Why should you become a Big Data Architect?
While there are several reasons for becoming a Big Data Architect, we have listed the most common ones here.
As companies depend heavily on their big data analysis to plan future business plans and projects, they require expert data architects to help them formulate and consolidate those ideas. This has created a lot of opportunities for data architects in the big data field.
As the technology evolves and becomes more complex while continuously integrating with other technologies, the industry will continue to grow. Companies will need experts in the big data field for niche job roles and responsibilities.
As you have already seen, the pay structure for a big data architect is way more than that of many other job roles in the same field. And you have also seen how it will grow as your career grows. Just make sure to keep yourself updated and on track.
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This job is a challenging one and requires you to multitask, handling many responsibilities at once. But this can also be a chance for great personal growth as the learning curve will be continuous.
Also Read: Data Scientist Salary in India
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The job of a Big Data Architect is now a mandated requirement for companies dealing with data on a large scale. You will be the person who will develop the architecture to help organizations get the data, when they need it and how they need it, without a glitch. It is an interesting and empowering field, and if you want to earn the highest salary possible, an online course with upGrad is the right option.
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What is the difference between Data Architects and Data Engineers?
The advent of the Internet and the popularity of smartphones have led to a massive rise in the generation of data. Companies are in dire need of experienced people who can perform any given task diligently. The two popular job roles in data are that of a Data Engineer and Data Architect. Usually confused as the same, the roles of the two are different. The main job of Data Architects is to visualise and design the data in an understandable framework so that Data Engineers can then build a digital framework. On the other hand, Data Engineers collect, maintain, and convert data for Data Analysts to draw meaningful insights.
What is the use of Big Data?
Big Data refers to all kinds of information collected from sources like news or organisations. It has become essential in the current times. Companies use Big Data to derive insights about customer preferences and use it to serve them best, thus improving profits. It is also used to forecast demand and plan ahead based on past demand patterns. Big Data is also helpful in the medical field to identify disease signs by doctors and help provide timely treatment.
What are the disadvantages of Big Data?
Big Data has taken the world by storm by helping companies and governments understand various patterns with the help of data. These insights have helped serve customers better and enhance the profitability of the companies as well. This is why companies are using Big Data to improve their business operations. Despite so many advantages, it also suffers from limitations, such as violating customers' privacy, manipulating customer records, rapidly changing technology, cybersecurity risks, hardware need for storing data, and high maintenance costs