5 Chief Big Data Careers In-Demand

As the internet of things takes the business world by storm, professionals in data science need to be prepared to deliver on what the industry expects from them. Those who keep honing their skills will lead the digital era. 

The demand for big data professionals is rising. According to Statista, the market for Big Data will grow by 103 billion by 2027. BIG DATA ANALYTICS is a golden goose for all industries, from healthcare to IT to manufacturing. 

To unlock the potential offered by Big Data career, you must know the types of roles therein and tasks performed by each cog. Here is a quick list of five main Big Data roles highly in-demand. No Big Data project can do without them.

5 Major Big Data Career Roles

1. Big Data Visualization Specialist
2. Big Data Architect
3. Artificial Intelligence Developer
4. Big Data Engineer
5. Big Data Scientist

Big Data Visualisation Specialist

Data is nothing without information being extracted from it. It requires the power of visualization. Visualizing data is critical to capitalizing on Big Data. These are the professionals who can tell the story being reflected by the data. 

Other than making associations and connections between disparate information, they excel in instruments such as D3, Carto, Tableau, and others. 

Big Data Visualization experts are versatile and inquisitive. Their major job responsibilities include: 

• Develop analysis based on data visualization. 
• Guide decision-makers based on analytics 
• Understand data flow – source and interventions made to ensure data is right and reports correct information
• Work with analysts, business strategists 

Big Data Architect

Hadoop specialists are instrumental here. They are Big Data planners. They devise the structure and conduct of Big Data arrangement an organization uses while innovating based on their experience on the way. 

Big Data professionals working as Architects are a significant bridge between data scientists and engineers. Any business aiming to capitalize on data will need these modelers who can model the total lifecycle of data collection to analysis into a Hadoop arrangement. 

They must have hands-on experience and knowledge of Hadoop tools and technologies. Their main responsibilities include: 

• Conceptualize and design Hadoop Big Data arrangement
• Design technical architecture
• Gain a complete understanding of the Big Data ecosystem (technologies and use cases) 
• Manage databases and data on Hadoop or other Big Data platform
• Participate in necessity investigation, engineering structure, and testing deployment

AI Developer

Big Data is a close relative of Artificial Intelligence. Any intelligent machine learning system requires a huge amount of data. It’s well-accepted now within Big Data industry that if professionals in Big Data go about getting certified in Artificial Intelligence, they can expect immediate exponential career growth. They are masters in a wide range of programming dialects, such as Prolog, C++, Java, Python, and more. Along with programming prowess, they have strong analytical and logical faculties. Their job responsibilities include: 

• Develop customized applications using programming languages
• Develop ETL or ELT processes to get the right data in a comprehensible format
• Understand data sources, structures, and their relation

Big Data Engineer

They clean and convert raw data into quality data. The job opening for Big Data Engineers will rise. They are involved in controlling data with SQL, R, Hadoop, Hive, Python, Spark, and other languages. They are innovative and have a predictable way to deal with information transformation. Their main responsibilities include:

• Performing information demonstration and modeling
• Evaluate new data sources
• Handle a large amounts of raw data and convert it into comprehensible bits
• Communicate between executives and the engineering team 

Big Data Scientist

From big data professionals, data scientists are the ones who have to play the jack of all trades. They have solid software engineering capabilities, as well as good mathematics and statistics. They are also strategists who are good at understanding supply chains and business requirements. They are involved in: 

• Developing predictive analytics models
• Analyzing complex data points to make business decisions
• Apply their strong software engineering, mathematics, and applied science knowledge to converting data into business value

These were the main big data career paths that are in demand. Bear in mind, along with learning tools and technologies, a career in Big Data is as much about understanding business. Innovation comes from a combination of both.