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Most of the services and applications we use today rely on immense blocks of data for successful operation. Social media, for example, is built almost entirely on big data, which allows it to optimize news feeds and recommendation algorithms.
Of course, big data uses don’t stop there - anything from predicting user demand and personalizing ads or service offers, to improving AI, streamlining internet searches, and improving the efficiency of urban infrastructure requires big data manipulation and analytics.
In order for such complex datasets to be used successfully, hundreds of thousands of people work on gathering, extracting, collating, structuring, and interpreting said data. The amount of data in circulation is growing exponentially, so it’s no wonder that big data jobs are in increasingly high demand.
Based on the latest information, we can expect the big data market to reach $103 billion by 2027. As it grows ever larger, so does the need for more data scientists. As such, it’s not surprising that the US Bureau of Labor Statistics predicts that data-related jobs will grow by 28% by 2026, creating over half a million new positions in the field.
With such a promising future, job seekers are flocking to this field, clicking on every big data ad in search of employment. We’ll go over the most lucrative positions in the market, as well as prerequisites, salaries, and responsibilities for each.
What is Big Data?
Big data is a now-ubiquitous term that’s thrown around whenever tech giants like Meta, Amazon, or Microsoft are mentioned. The term ‘big data’ was first coined by Roger Mougalas from O'Reilly Media in 2005. The same publication fostered the concept of Web 2.0 - an idea that largely shaped how we think about the Internet today.
According to the Google Books Ngram Viewer, which tracks the usage of a particular term in published books, the global use of the phrase “big data” exploded in 2009, and has remained pervasive ever since.
But what does the term big data actually represent? In essence, it refers to incredibly large and complex information sets that are impossible to analyze through traditional methods and data processing applications. The data can cover pretty much anything: User behavior, internet searches, medical information, shopping habits, fintech data, and more.
Big Data has three defining properties, dubbed as the “three Vs”: Volume, velocity, and variety.
Volume
Big data’s defining characteristic is, naturally, its volume. The sheer amount of data being collected every minute is constantly rising, requiring more data scientists and a stronger processing infrastructure as time progresses. According to current big data estimates, 2.5 quintillion bytes of information are created daily - 30 times more than in 2005. As the number of IoT devices and apps we use increases, so does the amount of data created.
Velocity
Compared to traditional, “small” data, big data is created and processed much more quickly, in real-time.
Variety
Big data does not come in a single, uniform format. Instead, it includes an immense range of configurations that need to be transformed to offer information on things like click rates, financial transactions, watch time, emails, text messages, and much, much more.
Of course, big data isn’t as dandy as all that: There are massive privacy and security concerns when it comes to how Big Tech uses big data, which is why an increasing number of people now actually read the privacy policy of any service they plan to use.
Now that we’ve covered the basics of what big data is, let’s get into what data scientists do, the various positions this industry entails, and whether a big data career is worth the trouble.
Top Big Data Careers
As mentioned, the demand for trained data scientists who will collate and make sense of these huge treasure troves of information is on a constant rise. Huge companies like Amazon, Meta, and Google compete constantly to better utilize the available data and foster growth, engagement, and profit. People with Google big data jobs are the ones that made the search engine as complex and advanced as it is today.
Unlike the IT sector at large, which has experienced some saturation after the initial 2000s boom, the field of big data still has thousands of vacancies. Indeed, the largest job posting site in the world currently has nearly 46,000 job openings for big data analyst positions.
What’s more, big data jobs come out near the top on any IT job salary comparison. Data pulled from ZipRecruiter and Talent.com shows that the average salary for big data analysts is over $130,000 per year (around $63 per hour). That’s more than eight times the US federal minimum wage.
While it’s true that you need a degree in computer science or similar fields in order to land employment in this field, there is room for entry-level jobs and a career in data mining. Thanks to the advancement and popularization of various data processing tools, the job has become more approachable. This includes using Google Analytics for quick, easily accessible data or analyzing data through Python or R - a programming language that allows complicated analysis to be done with just a few lines of code.
Still, don’t expect to get hired without advanced IT knowledge, although different positions vary in terms of requirements. Another important thing to note is that nearly all the positions outlined here can be done both onsite and from a remote location, which is a great asset given the circumstances.
Data Scientist
Although the term “data scientist” is often used to describe all big data job titles, it’s actually a very specific job. Their work is at a cross-section of computer science, mathematics, and statistics, and they’re usually on the frontlines of big data analytics. Data scientists are in charge of creating new processes, prediction algorithms, and models for interpreting data. Additionally, they are tasked with informing important business decisions based on their analyses.
Qualifications
An advanced degree (such as a Master’s or PhD) in computer science, coupled with extensive knowledge of data mining and statistical analysis is often required for this position. On top of that, database management and AI expertise are welcome too, as well as a few years of experience in the field.
Average Salary
According to the job posting site Indeed, the average salary for data scientists in 2021 is $113,821. Glassdoor, a popular company review site, puts the average salary at $117,212 in the United States. Some of the highest-paying data scientist jobs earn up to $130,000 per year.
Big Data Engineer
Often conflated with data scientists, data engineers actually have a different position in the overall big data hierarchy. While data scientists largely focus on interpreting and structuring data sets, data engineers are the ones that collect and organize the data in the first place. They aim to find patterns and trends in data which would allow them to group the information in an understandable way and build data pipelines. These pipelines are sets of processing elements which “cleanse” data from irrelevant elements and put the end product at the disposal of analytics departments.
Qualifications
Besides a degree in computer science or a related field, data engineers are required to possess extensive coding knowledge, including languages such as C#, Java, Python, R, Ruby, and SQL. Knowledge of Linux systems and SQL databases is also crucial for this position, coupled with familiarity with Hadoop - a Java-based framework for processing big data. Of course, substantial experience in the field is also a must.
Average Salary
We aggregated salary information from multiple job posting sites, and found that the average salary for big data engineer jobs moves between $92,000 and $118,000 per year.
Data Architect
A data architect’s main responsibility is to visualize and design data management frameworks. This framework pretty much defines how data is collected, structured, cleansed, and controlled within the enterprise. Furthermore, data architects are the ones that actually translate business-level goals and requirements into practical terms.
Data architects could be defined as an advanced version of data engineers, with whom they often work closely. Data architects are responsible for creating a blueprint for the data management framework, while data engineers are tasked with building that framework.
Qualifications
If you’re aiming for a data architect position, you need to have a bachelor’s (preferably higher) in computer science, computer engineering, or a related field. Similar to data engineer qualifications, you should also possess coding and big data management knowledge, in addition to system development and data modeling.
Average Salary
As one might expect, the average big data salary for data architects is slightly above that of engineers Again, the figures differ between job posting sites, but some ballpark numbers are: $121,000 (Payscale), $118,000 (Glassdoor), and $132,000 (ZipRecruiter).
Data Analyst
Data analysts could be regarded as foot soldiers in the company’s big data infrastructure. A Data analyst’s main job is to, well, analyze the collected data. They work both in collecting said data (run surveys, capture data) and interpreting it (finding patterns). A significant portion of a data analyst’s day-to-day is spent creating reports for other departments within the company and business clients.
Analysts turn the patterns detected in data into a narrative relayed through reports that offer insights for people higher-up in the hierarchy.
Qualifications
Data analysts are the closest to big data entry-level jobs. Unlike other more demanding positions, an advanced degree in computer science usually isn’t mandatory (sometimes you can get hired even without a BA). However, you do need to know your way around SQL databases, Microsoft Excel, and some knowledge of statistics and basic programming. Of course, more demanding (and better paid) data analyst positions might have stricter requirements.
Average Salary
On average, the salary for big data analyst jobs moves between $61,000 and $69,000 per year, while the highest-paying analyst jobs can bring over $80,000/year. This is considerably less than what other positions we covered here offer but is offset by significantly less demanding qualifications. If you’re looking to get your foot in the big data door, consider starting off as a data analyst.
Database Manager
The terabytes and petabytes of data processed by companies are stored in sprawling databases. Database managers, as the name suggests, are in charge of keeping those databases running properly. This includes evaluating data sources, monitoring data loads and usage requests, generally taking care of the database’s health, and troubleshooting any issues that may arise. On top of that, they act as supervisors of sorts for all database teams.
Qualifications
Naturally, database managers need to be adept at using various database software like MySQL, Oracle, or IBM DB2. As for education, a bachelor’s degree in information technology or higher is usually required, as well as a few years in a related management position.
Average Salary
Information on the average salary for database managers differs greatly between sources. According to Payscale, the average salary is around $58,000 per year, Glassdoor puts it at $75,500, while on Indeed, the median salary for database managers is $61,000/year. You can database management to be similar to big data analytics jobs, salary-wise.
Business Intelligence Analyst
Business intelligence or BI analysts put all the data to use to produce business solutions based on the data collected that will lead to the company’s growth and maximization of profits. Meta leveraging user behavior data to change its algorithm and keep users engaged is a good example of using insights gained from big data.
BI analyst responsibilities also entail maintaining the integrity of collected data, meaning they keep tabs on whether the collected data is still valid and accurate.
Qualifications
With BIAs in charge of such important decisions, it’s no wonder that the required qualifications for this position are somewhat intimidating. First of all, candidates are required to have a bachelor’s or master’s in Business Intelligence. On top of that, a BIA should have a background in cloud computing, data storage, data mining and security, as well as experience with SQL and Hadoop.
Average Salary
Among big data jobs, the salary for a business intelligence analyst falls on the lower-to-middle end, with a $69,000 - $89,000 per year range. Of course, the annual salary for this position can cross the $100,000 threshold for senior data positions.
Frequently Asked Questions
What are the jobs in big data?
There are plenty of jobs in the field of big data, with the most commonly known (and lucrative) ones being:
Data scientist
Big data engineer
Data architect
Data analyst
Database manager
Business intelligence analyst
Is big data in demand?
Very much so. The job posting site Indeed has over 46,000 openings for big data positions in the US alone. The current demand isn’t going anywhere either, as the big data market is projected to reach $96 billion by 2026 and create over 500,000 new jobs in the field by 2028. If you’re considering careers in data mining or analytics, now is definitely the time to get in on the action.
Does Big Data pay well?
Yes, most big data positions, especially senior ones, are extremely lucrative. The average yearly salary for big data positions is $130,000, which translates into $62.5/hour.
Is big data easy to learn?
Yes and no. While you could land an entry-level data analyst position with some knowledge of SQL databases, Excel, and basic programming, advanced positions are somewhat demanding and usually require at least a BA in computer science. As for the other skills, most positions require you to be good at data visualization, mining, and familiarity with various tools and frameworks such as Apache, MySQL, Oracle, Hadoop, and so forth.
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