Here we are to see the Data Job Titles.
In the aspiring world of tech-savvies, we are approaching the future. And the way of living has been changed over the years. Now, the lifestyle is more inclined to comfort and innovation, rather than just old ways of doing things. Do you know? Let alone the face of education has changed vastly since last year due to the corona outbreak. Humans tend to adapt to the things around them for survival and comfort. In certain ways, humans have developed instruments and appliances for every big or little task at hand. And thus, applying technology to make the work less hectic and efficient has been our pride for a millennium.
And today, the world looks up to handling data to manage and excel in the fast-paced growing industries, finance, and marketing. You may ask how data management helps us? How do data surround us? Well, to start data is not only a collection of information. It is the raw form of information from which another useful set of information can be derived.
And to know and understand the key aspects of data handling and management proves to be an essential skill anywhere you work. You know, it has the plus point that data jobs have high-paying job titles if you have mastered the relevant skills used in the field. Are you thinking, you have to be good with computers to do data jobs? The answer is NO. It will be a bonus if you are acquainted with computers and programming but, the field of data science is much more than only dealing with a huge amount of data on a computer screen.
The data-driven field seems to be based on computer science. But no, it is only a part of it. Data science or big data analytics as a subject is pillared by five sub-sections computer science, mathematics, statistics, economics, and management. How to prepare for a field which has these many domains and co-domains? What job title you should go for in the field of data? How to cope up with jobs and tasks in data science if you are not a programming enthusiast? Don’t worry, sit tight. And as we go ahead in this article, all your questions will get answered. First, let’s talk about what the big data industry is.
Big Data Industry
Technically, the hottest field out there right now is big data which has proved to revolutionize in almost every field. Claimed as the most promising profession around the world right now. In the last decade, people have acknowledged that to sustain a profitable and successful business or working as a big corporation needs the evaluation of massive data received in a single day. The evaluation includes mining, structuring, management, and providing valuable insights into data.
The industry has grown rapidly in the past few years and is still growing as we speak. The demand and need for the working of big data analytics is the reason why the weightage of big data is in the spotlight for both academics and industry.
What are the roles an expert in big data imparts? There are various titles under big data. By name, the field is vast in itself, which further collides with other fields like business and management. Well, the work involves a lot of techniques, tools, and time. But the main idea is if you are a seeker of precious things, you can seek valuable information for the company you work for. And if it helps, you can study social networks, forecasting, machine learning, and many more interesting concepts.
Now, is big data for you? At first, when you’ll learn the prime aspects or basics in data science, things can be overwhelming. You may find a co-domain you’ll fell in love with, and other/s domains may be boring. But if you hold a bit longer then, you’ll get a hang of it. Simply, the people working in big data try to find trends in the data using mathematical, statistical, and programming tools. And thus, a role in big data is to collect, organize, analyze, and process the data. Let’s see the job roles in big data to find out which job is made for you.
List of Job titles
There are numerous fields under big data, the three broad categories are Scientists, Analysts, and Engineers. Let’s try to understand the working of a particular domain then, we’ll discuss the co-domains or other jobs in the field.
1. Data Engineer
Also known as the data architect. As the job goes for any engineer, the base of an engineer is to design and create innovative ideas. In the context of data, engineers are those who ensure designing, building, and managing information, or as said in the field massive amount of data within an infrastructure. Data engineers serve various responsibilities engaging with data scientists.
That is data engineers build and test a huge data pipeline for the data scientists to run several concepts and rules that are stable and optimized to get desired results. The role of a data engineer also includes upgrading the current data system with newer and faster technology to produce efficient results. Well, that was a lot to process in technical terms. In simple words, data engineers help the organization or data users, in general, to access data for what they need. They point the users in the right direction to obtain the results in a timely fashion.
Data engineering is the most important because they make sure the big data ecosystem of a firm or organization runs smoothly. And additionally, without these people, the data scientist will get stuck and won’t be able to carry out the analysis. The average annual salary of a data engineer is $137,776 and can vary according to place & experience.
What does it take to be a data engineer?
The necessity of the job is to acquire a computer science degree with mastery over at least one or few technical tools like Pig, Hadoop, Hive, MySQL, Cassandra, etc. Most of the works deal with programming so, gathering a collective knowledge of many programming languages like R, Python, Ruby, Java, and Matlab are the basics. The other skills include the usage of tools like ETA, data APIs, data modeling, and data warehousing.
2. Data scientist
Here is the best job title that focuses on work-life balance. When we talk about data scientists the topic gets overlapped with data analysts. The reason why? Because they are put under the same domain in the field – to gather insights out from the data. But how close these job titles work data analyst is considered to be a junior role to the data scientist. Data scientists’ main goal in a company is data crunching. However, it is more than that. A data scientist has the following responsibility to comprehend business challenges, create actionable insights into data, and convey their findings in business. Data scientist stands with queries in the data and also try to resolve them.
And one key aspect of the job is to predict future analytics. They make work of coding to do predictive analytics on large amounts of structured or unstructured data to help in designing future strategies. In short, data scientists work to take concerned data-driven decisions by utilizing mathematical models, statistical concepts, and programming.
The average salary of a data scientist is $100,560 in the US and may increase in the coming future as companies have started to realize the importance of big data. A data scientist may not be a good field to start with but with excellent skills, you can learn the ways of work in no time.
What skills does a data scientist have?
Data scientist is a critical job. Thus, people in the field need to be an expert in several programming languages such as R, SQL, Python, Hive, Pig, Spark, and Matlab. This job title required me to have higher degrees in subjects as mathematics, statistics, or Big Data Analytics as introduced in recent years.
Now, let’s talk about the key point where the data scientists and analysts converge i.e data scientists adhere to machine learning. They work with statistics techniques and machine learning to give descriptive predictive analytics. And in between the process, they find efficient algorithms in machine learning.
3. Data Analyst
The second most in-demand job title in the big data industry is a data analyst. As mentioned above, data analyst overlaps with data scientist job. Though data analysts are responsible for the major work on data systems, which includes visualization, transformation, and manipulation.
In the big data industry, the work starts with data engineers & architects who operate the data before the collection of data. And data scientists and data analysts are there to do the required operations. The direction of work for a data analyst is to acquire the massive data, to process and then, summarize it for presenting. A good data analyst is curious and is ready to investigate the data from multiple angles.
And hence, operations are done to clean and transform data to find trends in it. Data analysts have a strong role in the organization. They mine the data and represent the findings after getting them. The secret key of a data analyst is to polish exploratory work into explanatory work. The average salary of a data analyst is $70,033 and can go up to $108,669 or more.
An adjacent field to data analytics: Business analytics
The basic role of a business analyst is to show how big data is linked to actionable insights for business growth. As the name suggests, you can say it is a combination of business and analytics. This role is quite different than any other data science job title. Business analytics requires examining and analyzing business processes. And this is the job where you don’t need to be proficient in programming. There can be a different data analyst department that helps business analysts. The main objective of a business analyst is to explore collected data and create reports concerning business trends and find solutions if encounter any issues.
Those are the main domains of the big data industry. There are many other job titles too, namely Database administrator, machine learning engineer, data and analytics manager, statistician, big data engineer, business intelligence jobs, and many more which revolves around the operation, working and processing of data.
The skills required in particular fields may or may not differ yet have the basic knowledge of big data technologies, tools, and processing. The field is still emerging so, new tools get updated from time to time. Thus, you should be needed to be updated with trends and tools in the big data industry.
Conclusion
In the realm of science and advancement, big data have the most important prospect nowadays. Because the company’s success is governed in the terms of data and data-driven decision making. The big data industry is exciting in itself which makes it an interesting field to enter. The jobs are quite impressive and come in a great package and if you got the right skills, you can easily shine in the field.
And along with a high-paying job title, data jobs provide good security, position, and balanced work-life in comparison to other IT jobs. Though the big data industry demands people having high skills, no pain no gain. Therefore, there are numerous post-secondary degrees. To help the upcoming generation to be more skilled than ever.
FAQs
1. Which job title is the best in data science?
Given the pay, workload and skills required the best job is data scientist. The growth of the field has also represented every other company wants to have data scientists in their workspace to gain more and more profit. Because with a perfect harmony of all three domains of big data i.e data scientists, data analytics, and data engineers can change the whole outlook and raise the sales or profit of a company in just within a year.
2. Is data sciences dying field?
No. Not at all, instead, the field of data science has attracted a vast majority of people who want to have a part in business and analytics. This is an evolving field, and seems like will go on like this for a millennium to come.
