Big data is transforming businesses and driving growth throughout the global economy.
Businesses have seen an incredible benefit in using big data to protect their databases, aggregate large volumes of information, and make informed decisions that benefit their organizations. Therefore, it’s clear how big data has been able to range across many sectors. The financial industry, for example, uses big data as a crucial tool to make profitable decisions, while other data organizations consider it an asset to protect against fraud and detect patterns in large datasets.
To understand the importance of this field, it is critical to know what big data is and the ways in which it has become an asset to society as a whole.
What is Big Data?
Big data is a field that deals with massive data sets that are too complex to manage using traditional data management methods. Organizations mine unstructured and structured data, leveraging machine learning and predictive modeling techniques to extract meaningful insights. With these findings, managers are able to make data-driven decisions that solve key business problems.
There are several technical skills that individuals must acquire to succeed in this field, including data mining, data visualization, programming, and other analytics skills. Due to the various challenges in learning these skills, the need for professionals in this field continues to increase, making the big data field a sought-after career path.
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Is Big Data Still in Demand?
The U.S. Bureau of Labor Statistics (BLS) anticipates data-related occupations will grow by more than 31 percent by 2030, creating a plethora of new jobs in the same time period. Increasingly, top companies are in need of qualified professionals to fill those emerging roles. However, professionals with these specialized skills are difficult to find, meaning data jobs pay quite well for those with the right expertise.
Salaries for big data careers are increasing just as quickly as the demand for skilled professionals. Many of these jobs report compensation well into the six-figure range and above market value in order to compete in the talent war, according to research from IT jobs site Robert Half Technology (RHT).
Is a Degree Needed for a Big Data Career?
A majority of these jobs require candidates with both experience and advanced degrees. In a fast-growing field, that’s not easy to find. Eighty-one percent of all data science and analytics job postings seek workers with at least three years of prior work experience, and 39 percent of these roles—the highest-paying ones, in particular—require a relevant master’s degree.
An important factor to remember is that senior data analysts, business analysts, and other big data professionals will most likely differ in the kinds of degrees they pursued to get into the field.
Master of Science degrees are the overarching similarity for these professionals;, however, their education can vary in what areas they focus on, such as data science or business analytics. Regardless of which specialization they choose, individuals with a relevant master’s degree in big data can look forward to generating a successful career in this incredibly lucrative industry.
But which big data careers pay the highest? Here’s a look at the most coveted positions, their salaries, and the skills you’ll need to qualify.
Top 10 Big Data Careers
Big data’s impact on various businesses has further catapulted the job opportunities available for professionals in the field. Here are ten of the top careers within big data for employers and job seekers alike. (All salary data is sourced from Robert Half’s 2022 Salary Guide. The salary ranges below represent starting salaries in the 25th to 75th percentiles.)
1. Big Data Engineer
Annual Salary Range: $115,250–$168,250+
Big data engineers are similar to data analysts in that they turn large volumes of data into insights that organizations can use to make smarter business decisions, but they’re also tasked with retrieving, interpreting, analyzing, and reporting on a business’s data—which they typically have to gather from a variety of different sources.
These professionals are also often responsible for creating and maintaining the company’s software and hardware architecture, including the systems and processes users need to work with that data.
2. Data Architect
Annual Salary Range: $127,750–$176,500+
These professionals are tasked with designing the structure of complex data frameworks, as well as building and maintaining these databases. Data architects develop strategies for each subject area of the enterprise data model and communicate plans, status, and issues to their company’s executives.
3. Data Security Analyst
Annual Salary Range: $115,000–$166,750+
Data security analysts perform security audits, risk assessments, and analysis to help make recommendations for enhancing data systems security. They often research attempted breaches of data security and formulate security policies and procedures to rectify security weaknesses.
4. Database Manager
Annual Salary Range: $116,250–$165,500+
Database managers identify problems that occur in databases, take corrective action to remedy those issues, and assist with the design and physical implementation of storage hardware and maintenance. They are also responsible for the storage and analysis of data within their organizations.
These professionals work closely with database developers and often provide guidance and training to lower-level staff.
5. Business Intelligence Analyst
Annual Salary Range: $94,500–$141,500+
Business intelligence analysts turn companies’ data into insights that executives can use to make better business decisions. These professionals often respond to management’s requests for specific information, but might also be expected to scrutinize data independently to find patterns and trends.
Business intelligence analysts should have a strong background in analytical and reporting tools, several years of experience with database queries and stored procedure writing, as well as online analytical processing (OLAP) and data cube technology skills.
6. Data Scientist
Annual Salary Range: $113,500–$162,500+
Data scientists design and construct new processes for modeling, data mining, and production. In addition to conducting data studies and product experiments, these professionals are tasked with developing prototypes, algorithms, predictive models, and custom analysis.
Previous work experience in a similar position is usually required, and data scientists should be skilled in different data mining techniques, such as clustering, regression analysis, and decision trees.
7. Data Modeler
Annual Salary Range: $87,000–$134,750+
These professionals turn large volumes of data into insights, such as micro and macro trends, which are gathered into reports for businesses. Data modelers must be skilled in both information science and statistical analysis and should have proficient programming skills.
Data modelers often choose to specialize in a particular business area, which makes it easier to find useful data trends for their employers.
8. Database Developer
Annual Salary Range: $101,000–$140,750+
Database developers are responsible for analyzing current database processes in order to modernize, streamline, or eliminate inefficient coding. These professionals are often charged with monitoring database performance, developing new databases, and troubleshooting issues as they arise.
Database developers work closely with other members of the development team. They’re often required to have prior experience with database development, data analysis, and unit testing.
9. Database Administrator
Annual Salary Range: $82,750–$124,500+
These professionals are responsible for monitoring and optimizing database performance to avoid damaging effects caused by constant access and high traffic. They also coordinate with IT security professionals to ensure data security. Database administrators typically have prior experience working on database administration teams.
10. Data Analyst
Annual Salary Range: $87,500–$126,250+
Data analysts work with large volumes of data, turning them into insights businesses can leverage to make better decisions. They work across a variety of industries—from healthcare and finance to retail and technology.
Data analysts work to improve their own systems to make relaying future insights easier. The goal is to develop methods to analyze large data sets that can be easily reproduced and scaled.
How To Start A Career in Big Data
Big data is a fast-growing field with exciting opportunities for professionals in all industries and across the globe. With the demand for skilled big data professionals continuing to rise, now is a great time to enter the job market.
If you think that a career in big data is right for you, there are a number of steps you can take to prepare and position yourself to land one of the sought-after titles above. Perhaps most importantly, you should consider the skills and experience you’ll need to impress future employers.
The highly technical nature of skills needed for big data careers often requires advanced training and hands-on learning experience. Seeking a graduate education in your area of study can be one of the best ways to develop this expertise and demonstrate your knowledge to future employers. Northeastern’s MS in Data Science and MS in Business Analytics programs, for example, are designed to equip students with strong analytical and technical skill sets, as well as allow them to build relationships with industry leaders and peers in the field.
Switching Careers Into Big Data
Even if your background is in a completely unrelated field, it’s still possible to make the switch to big data and change the trajectory of your career. If you’ve been pondering whether you should change careers, start looking at the transferable skills that you might already possess and the required skills that you’ve yet to develop.
To close this gap and sharpen your big data skills, you may want to look into an advanced degree program such as Northeastern University’s Align Data Science program. This program is designed specifically for students with an undergraduate degree in an unrelated field and provides the foundational knowledge and experience necessary to begin a career in big data. Alternatively, Northeastern also offers a Data Analytics Engineering program as well as an accelerated alternative for students who are looking to acquire rigorous analytical skills and research experience in preparation for a doctoral program in health, security, and sustainability.
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Editor’s note: This post was originally written in July 2017 and has since been updated for accuracy.