Watch Out for the Top big Data and Data Science Roles in 2022

Data science and big data support a wide spectrum of job opportunities, explore the top data science roles for 2022

The rise of data science has come to the accompanying explosion in roles in some way that involves data. No wonder it is one of the hot and progressive fields of technological applications in current times. Perhaps the best job market right now converges in the field of data science. Meanwhile, this emerging field is revolutionizing technology and industries alike. As industries across all verticals become more data-driven, it influences the jobs market and the skills that are required. As we discover new data touch points and ways to analyze them, the society we reside in, our daily lives, and the nation's economy become more reliant on the data. This is also why data science and big data support a wide spectrum of job opportunities.

While data scientist is heralded as the sexiest job of the 21st century, in recent years, job roles like data architect, data analyst, are gaining more traction. Let's have a quick overview of the most common job roles in data science and big data.

• Data Statistician

Average Pay in India: INR 518,935

A Data Statistician collects, analyses, and understands qualitative and quantitative data by using statistical theories and methods.

Skills: Database systems (SQL and NoSQL), Distributed Computing, Data editing and cleaning, Analysis tools (MatLab, R), Statistical software (SAS, SPSS)

• Business Analyst

Average Pay in India: INR 700,000

A business analyst is proficient in the skill of linking data insights to actionable business insights and can use storytelling techniques to spread the message across the entire organization. 

Skills: SQL, MS Office, Storytelling, conscious listening, Power BI 

• Data Engineer

Average Pay in India: INR 830,088

A Data Engineer focuses on the development, deployment, management, and optimization of data pipelines and infrastructure to transform and transfer data to data scientists for querying.

Skills: Programming languages (Java, Scala), NoSQL databases (MongoDB, Cassandra DB), frameworks (Apache Hadoop)

• Data Administrator

Average Pay in India: INR 682,476

Data Admin has to ensure that the database is accessible to every stakeholder in the organizations, is performing legitimately, and that the necessary safety measures are in place to keep the stored data safe and immune to hacking.

Skills: ERP, Data modeling and design, Java, HTML, Database management system (Oracle 11g, Microsoft SQL Server, IBM DB2, Sybase and MySQL), Knowledge about operating systems (Windows, Linux, UNIX), Management Of Information Systems (MIS).

• Data Architect

Average Pay in India: INR 1,983,996

Data Architects are charged with the responsibility of designing, creating, deploying, and managing an organization's data architecture. They have to design blueprints for data management framework to integrate, centralize and maintain data sources.

Skills: RDMSs (relational database management systems) or foundational database, Programming languages (Python, Java, C++), Hadoop technologies, like MapReduce, Hive, and Pig, ETL (extract, transform, load), Data modeling (Impala, Oozie, Mahout, Flume)

• Data Analyst

Average Pay in India: INR 427,021

A Data Analyst works on processing and performing mainly statistical analysis on existing datasets. Apart from that, a data analyst is responsible for data querying, forecasting to look for relationships, patterns, trends in data. 

Skills: Programming skills (SAS, R, Python), statistical and mathematical skills, data wrangling, data visualization (Tableau, Qlik), spreadsheet tools like Microsoft Excel or Google Sheets.

Data Scientist

Average Pay in India: INR 10,00,000

A Data Scientist's work involves understanding an organization's goals and determining how data can be used to achieve those goals. A data scientist also designs predictive models which often incorporate machine learning and deep learning protocols; for the purposes of prediction, gleaning data, data analysis, etc.

Skills: Programming skills (SAS, R, Python), Statistical and Mathematical Skills, Storytelling And Data Visualization, Hadoop, SQL, machine learning, Predictive Modeling