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Big Data is the term that is circling everywhere in the field of analytics in the modern era. The rise of this term came about as the result of the enormous volume of unstructured data that is getting generated from a plethora of sources. Such voluminous unstructured data carries huge information which if mined properly could help a business achieve ground breaking results.

Hence, it’s wide range of applications has made Big Data popular among masses and everyone wants to master the skill associated with it to embrace the lucrative career opportunities that lies ahead.  For the data professionals, many companies have various open positions in the job market and the number is only going to increase in the future.

Reason of the craze behind Big Data

The opportunities in the domain of Big Data is diverse and hence its craze is spreading rapidly among professionals from different fields like Banking, Manufacturing, Insurance, Healthcare, E-Commerce, and so on.  Below are some of the reasons why its demand keeps on rising.

  • Talent shortage in Big data – Despite its every increasing opportunity, there is a significant shortage in the number of professionals who are actually trained to work in this field. Those work in IT are generally accustomed with software development or testing, while people from other fields are familiar with spreadsheets, databases and so on.

However, the required skill to load and mine Big Data is missing significantly which makes it the job which is up for grabs for anyone who could master the skills. Business Analysts and managers along with the engineers needs to be familiar with the skills required to work with Big data.

  • Variety in the types of jobs available – The term Big Data is somewhat holistic and could be misleading in defining the job descriptions for an open position. Even many people use this term in several situations without actually understanding the meaning behind its implementation. 

There could be several job types available in the market which has the term Big Data in it. The domain of work could vary from Data analytics to Business analysis to Predictive analytics. It makes easier for one to choose among the various types and train oneself accordingly. Companies like Platfora, Teradata, Opera, etc., have many opportunities in big data for their different business needs.

  • Lucrative salary – One of the major reasons why professionals are hoping onto the big data ecosystem is the salary that it offers. As it’s a niche skill, hence companies are ready to offer competitive packages to the employees. Those who wants a learning curve and sharp growth in their career, big data could prove to be the perfect option for them.

As mentioned before, there are a variety of roles which requires big data expertise. Below are the opportunities based on the roles in the field of big data.

  • Big Data Analyst – One of the most sought after roles in Big Data is that of a Big Data Analyst. To interpret data and extract meaningful information from it which could help the business grow and influence the decision making process is the work that a big data analyst does.

The professional also needs to have an understanding of tools such as Hadoop, Pig, Hive, etc. Basic statistics and algorithms knowledge along with the analytics skills is required for this role. For the analysis of data, domain knowledge is another important factor needed. To flourish in this role some of the qualities that is expected from a professional are –

  1. Reporting packages and data model experience.
  2. The ability to analyze both structured and unstructured data sets.
  3. The skill to generate reports that could be presented to the clients.
  4. Strong written and verbal communication skills.
  5. An inclination towards problem solving and an analytical mind.
  6. Providing attention to detail.

The job description for a big data analyst includes –

  1. Interpretation and the collection of data.
  2. To the relevant business members, reporting the findings.
  3. Identification of trends and patterns in the data sets.
  4. Working alongside the management team or business to meet the business needs.
  5. Coming up with new analysis and data collection process.
  • Big Data Engineer – The design of a big data solutions architect is built upon by the big data engineer. Within the organizations, the development, maintenance, testing, and evaluation of the big data solutions is done by the big data engineer. They also tend to have experience in Hadoop, Spark, and so on, and hence are involved in designing big data solutions. An expert in data warehousing, who builds data processing systems and are comfortable working in the latest technologies. 

In addition to this, the understanding of software engineering is also important for someone moving into the big data domain. Experience in engineering large-scale data infrastructures and software platforms should be present as well. Some of the programming or scripting languages a big data engineer should be familiar with are Java, Linux, Python, C++, and so on. Moreover, the knowledge of database systems like MongoDB is also crucial. Using Python or Java, a big data engineer should have a clear sense of building processing systems with Hive and Hadoop.

  • Data Scientist – Regarded as the sexiest job of the 21st century, a Data Scientist is the regarded as the captain of the ship in the analytical Eco space. A Data Scientist is expected to have a plethora of skills stating from Data Analysis to building models to even client presentations.

In traditional organizations, the role of a Data Scientist is getting more importance as the way the old-school          organizations used to work are now changing with the advent of big data. It’s now easier than ever to decipher the data    starting from HR to R&D.

Apart from analyzing the raw data and drawing insights using Python, SQL, Excel, etc., a Data Scientist should also be familiar with building predictive models using Machine Learning, Deep Learning, and so on. Those models could save time and money for a business.

  • Business Intelligence Analyst – This role revolves around gathering data via different sources and also compare that with a competitor’s data. A picture of company’s competitiveness would be developed by a Business Intelligence Analyst compared to other players in the market. Some of the responsibilities of a Business Intelligence Analyst are –
  1. Managing BI solutions.
  2. Through the applications lifecycle, provide reports and Excel VBA applications.
  3. Analyze the requirements and the business process.
  4. Requirements, design, and user manual documentations.
  5. Identifying the opportunities with technology solutions to improve strategies and processes.
  6. Identifying the needs to streamline and improve operations.

 

  • Machine Learning Engineer – A software engineer specialized in machine learning fulfils the role of a Machine Learning Engineer. Some of the responsibilities that a Machine Learning Engineer carries out are –
  1. Running experiments with machine learning libraries using a programming language.
  2. The production deployment of the predictive models.
  3. Optimizing the performance and the scalability of the applications.
  4. Ensuring a seamless data flow between the database and backend systems.
  5. Analyzing data and coming up with new use cases.

 

Global Job Market of Big Data

source: Datanami

Businesses and organizations have now put special attention to the full potential of Big Data. India has a large concentration of the jobs available in the big data market. Below are some of the notable points related to the job market of big data.

  • It is estimated that by 2020, that the number would be approximately seven lakhs for the opportunities surrounding the role of Data Engineers, Big Data Developers, Data Scientists., and so on.
  • The average time for which an analytics job stays in the market is longer than the other jobs. The compensation for a big data professional is also forty percent more than other IT skills.
  • Apache Spark, Machine Learning, Hadoop, etc., are some of the skills in the Big Data domain which are the most lucrative. However, hiring such professionals require higher cost and hence it is necessary that better training programs are provided.
  • Retail, manufacturing, IT, finance is some of the industries which hire big data expertise people.
  • People with relevant big data skills are a rarity and hence there is a gap between demand and supply. Hence, the average salary is high for people who are working in this field which is more than 98 percent than in general.

 

How to be job ready?

Despite the rising opportunities in big data, there is still a lack of relevant skills among the professionals. Hence, it is necessary to get your basics right.  You should be familiar with the tools and technique coupled up with the domain knowledge would certainly put you in the driving seat.

Tools like Hive, Hadoop, SQL, Python, Spark are mostly used in this space and hence you should know most of them. Moreover, one should get their hands dirty and work in as many productions based projects as possible to tackle any kind of issues faced during analysis.

Conclusion

There is a huge opportunity for big data and now is the best time than ever to keep on learning and improving your skills.

If you are willing to learn more about Big Data or Data Science in general, follow the blogs and courses of Dimensionless.

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