As more companies rush to become data-driven in business, Big Data continues to play a pivotal role. The need for workers capable of collecting, analyzing, and visualizing large amounts of information continues to grow exponentially.
According to a study by Markets and Markets, the data science market size is projected to grow from $95.3 billion USD in 2021 to $322.9 billion USD in 2026, a compound annual growth rate (CAGR) of 27.7%.
This growth will be driven by factors such as an increase in cloud computing infrastructure and services; proliferation of the Internet of Things (IoT); rising investments in research and development activities pertaining to artificial intelligence (AI) and machine learning (ML); and growing demand for data scientists across various industry verticals such as financial services, retail and consumer goods, manufacturing, and logistics.
As a result of this growth, the adoption of AI/ML solutions will only increase among enterprises, leading to the need for more experts in big data and data analytics.
Also read: Top Artificial Intelligence (AI) Software 2022
Top 6 Big Data and Data Analytics Jobs
Here then are six of the most in-demand Big Data jobs, along with their qualifications, certifications and salary ranges.
Data scientist
A data scientist uses computer programming, statistics, mathematics, and machine learning to analyze how data impacts your organization as well as how it can be used to solve problems. In addition, they use their skills to build models for predictive analysis and work on improving algorithms used by businesses.
Requirements and certifications
It’s possible to get into some entry-level positions without experience if you have relevant coursework or an undergraduate degree in computer science or math. However, to advance further, you’ll want to get certified through organizations like the Data Science Council of America (DASCA).
Responsibilities
Regardless of what type of data science you choose to specialize in, your duties will typically include collecting and cleaning datasets; determining which questions you should ask; and writing code, analyzing results, and creating reports that present findings.
Average salary
According to Indeed, the average salary of data scientists in the United States is $102,312 per year.
Also read: Best Data Analytics Certifications 2022
Data architect
A data architect, also known as a chief data officer (CDO), takes a high-level view of your organization’s data and how to use it effectively. The role includes collecting, classifying, storing, organizing, managing, and making accessible an organization’s data.
Additionally, a data architect focuses on improving business processes through tech solutions such as digital platforms like cloud computing.
Requirements and certifications
To become a data architect, you will need at least a bachelor’s degree in computer science or another relevant field. Also, a certified data management professional certification is seen as a plus.
Moreover, most employers prefer candidates with experience working with large amounts of data and knowledge of multiple programming languages, including Java, C++, and Python.
Responsibilities
Some duties include determining when to implement new technologies and systems, analyzing how current systems can be improved, and implementing new ways for employees to collect data. They may also create policies for handling sensitive information or developing new security measures for protecting private data from hackers or other cybercriminals.
Average salary
According to Payscale, the average salary of a data architect is $123,347 per year.
BI developer
A business intelligence (BI) developer is an expert software engineer who works with big data platforms to analyze raw data from an organization’s internal or external sources.
A BI developer uses tools like SAS, Oracle, SQL Server, and R to help companies develop strategies based on their data analysis. They also create reports that a company’s executives can use to make informed decisions about running their business.
Most organizations today use a combination of cloud-based and on-premises business intelligence solutions, which means that there will be plenty of opportunities for qualified BI developers over the next decade.
Requirements and certifications
A bachelor’s degree in computer science or a related field is the minimum requirement; having a master’s degree can increase your chances of landing a job and increasing your salary.
Additional certifications such as Certified Information Systems Auditor (CISA), Certified Information Security Manager (CISM), and Project Management Professional Certification (PMP) will give you even more advantages when applying for jobs as a business intelligence developer.
Responsibilities
The primary duty of a BI developer is to collect data from various systems within an organization and then transform it into meaningful information that can be analyzed. The results of these analyses are then presented back to decision-makers, so they can use them to make better decisions regarding operational processes, organizational strategy, financial planning, and sales forecasting.
Average salary
According to Salary.com, the average BI developer salary in the United States is $91,728 per year.
Also read: Best BI Tools 2022: Business Intelligence Software
Data engineer
A data engineer is an integral member of a development team who must collect, store, analyze, report on, and/or visualize various forms of data for business purposes. A data engineer can also act as a bridge between developers, who may be writing code, and data scientists, who may be analyzing or visualizing data.
Requirements and certifications
You need to have a bachelor’s degree in computer science or mathematics; however, some employers might prefer you to have a master’s degree. Having knowledge of Python and SQL is also essential.
And if you want to work with Hadoop—the open-source framework for processing large amounts of data—you should consider becoming certified through Cloudera, Hortonworks, Oracle, or MapR Technologies.
Responsibilities
As a data engineer, you will likely be tasked with collecting, storing, and analyzing huge volumes of structured and unstructured data. For example, you could develop ETL (extracting, transforming, loading) processes to cleanse raw information into something more useful for analysis, create reports using Tableau or other visualization tools, build dashboards for your company’s executives using QlikView or Power BI, or create predictive models using R language programming software.
Average salary
According to PayScale, the average salary of a data engineer in the U.S. is $93,272 per year.
Also read: Qlik Sense vs Tableau: Comparison
Data analyst
A data analyst is a professional who analyzes raw data to derive meaning and glean insights that can be used to improve business operations. These individuals can help businesses interpret information, from customer behaviors to employment trends, using a business intelligence platform and data visualization tools to work with their company’s raw data.
Requirements and certifications
To become a data analyst, you need at least some post-secondary education in statistics or computer science. Many employers prefer candidates who have a bachelor’s degree in these fields.
In addition to formal education, you should also be familiar with basic programming languages like Python and SQL. And while most employers don’t require it, certification from organizations like ISACA (International Information Systems Audit and Control Association) can also be helpful when looking for job opportunities.
Responsibilities
Depending on the level of education, training, or experience, a typical day for a data analyst might include working with Excel spreadsheets, analyzing large datasets using statistical software such as SAS or SPSS, writing reports about findings based on that analysis, and presenting those findings to upper management.
Average salary
According to Indeed, the average salary for a data analyst with one to five years of experience is $65,236 per year in the United States.
Decision scientist
A decision scientist refers to a professional who utilizes scientific methods, like data analytics, statistics, and machine learning, to solve business problems. The demand for decision scientists is expected to grow substantially during the next several years because businesses must constantly learn how they can make smarter decisions faster.
Decision scientists work with algorithms that help them analyze massive amounts of data quickly to determine which actions will produce optimal results. They use these insights to optimize their organization’s processes and operations.
Requirements and certifications
Decision scientists must possess at least a bachelor’s degree in statistics or mathematics, and they can earn certification through professional organizations like Decision Sciences Institute (DSI).
To be successful as a decision scientist, you should understand computer science fundamentals and have an aptitude for math and logic. It’s also essential that you have strong communication skills since you will likely be working with people from many different departments throughout your organization.
Responsibilities
Decision scientist duties include developing mathematical models, applying statistical analysis techniques, creating algorithms, identifying trends and patterns within datasets, building predictive models based on these insights, and interpreting results to make recommendations to other team members and stakeholders.
Average salary
According to ZipRecruiter, the average salary for a decision scientist is $97,546 per year in the United States.
The Future of Data Analytics and Big Data Professionals
Big Data and its many applications are only in their infancy, so the future is bright and vast, and with it comes an incredible array of opportunities for individuals skilled in data analytics. No matter the industry, with so many roles to choose from, there’s sure to be a place where your skills can shine.
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