As you have now seen in the past few years, there has been a soaring demand in terms of job growth in the field of data science. There is also a survey by the Bureau of Labor Statistics which forecasts about a 22% increase in opportunities in both data science data engineering. However, there is a distinct comparison that you need to know when you check data engineering vs data science. While it is true that companies are highly focused on generating, collecting, and analyzing of big data which is helping them run businesses, this also indicates that both data science data engineering fields will eventually see a lot of growth. To explore more about data engineering vs data science you can check the following article where we will also cover what is the difference between data science and data engineering and which one is the best option for your future.
What is Data Engineering?
Data engineering is a field where you will be focusing on the implementation, evaluation, and maintenance of data architectures. It also includes learning more about databases, data pipelines, and various other data processing systems. When you look at data engineering vs data science the main tasks that entail to engineering can be provided as follows:
- You help to optimize a larger internet retailer’s CRM (customer relation management) database.
- You tend to provide easy and smooth access to big data sets to data scientists’ MLP (machine learning projects) at social media giants.
- You ensure reliable pipelines of data from actuators and sensors for automated industrial manufacturing.
There are also certain skills that you need to attain in order to become a data engineer and they can be provided as follows:
- Data management skills where you learn more about tools such as data transformation, data management, data mining, and cloud computing
- Computer skills such as extensive knowledge of programming languages such as C++, Java, SQL, Python, and C language. You also need to be well aware of operating systems such as Windows, Linux, and Unix.
- Data visualization skills where you use tools such as Tableau and Matplotlib.
What is Data Science?
Data science is such a field where you leverage computer science, machine learning, and applied mathematics along with data management to extract various insights from large amounts of data that help build new tools and techniques. These insights that you get from data can help you in the following ways:
- Supporting your business decision-making
- Increase the research and development initiatives such as developing new metrics for analysis
- Or even form the basis of new products or services that you want to promote.
As a data scientist, you are also expected to learn certain skills that will be valuable when you go out for a job opportunity and these can be provided as follows:
- Understanding analytical tools such as Hadoop, Spark, and SAS can be helpful when it comes to extracting valuable information from an organized data set.
- Having experience working with unstructured data that comes from various sources and channels.
- Learning various languages such as SQL, Java, Python, and Perl.
Data Engineer vs. Data Scientist
There is a wide range of abilities required when comparing the duties and responsibilities of data scientists and data engineers. The differences between data science and data engineering are discernible from these diverse tasks and duties, even if there may be some overlap between them.
Roles and Responsibilities
Roles and responsibilities mainly help data scientists and data engineers to understand what their careers will consist of. As a data engineer, you will be mainly involved in building and optimizing the systems that allow data scientist to complete their job. On the other hand, when you compare data engineer vs data scientist, as a data scientist you will have to find meaning in a heap of data that data engineers mainly manage.
Data Scientist Roles and Responsibilities
A person is called a data scientist when they work on finding new insights from data that has already been prepared for them by data engineers. As a part of their job, data scientist need to conduct online experiments and use their knowledge of statistics, data analytics, and data visualization while also developing hypotheses to identify various trends. Identification of these trends will eventually help them in creating forecasts for the business.
As a data scientist, you will also be engaging with business leaders to help them understand their basic needs and present various complicated findings not just verbally but also in a visual manner. This should also be conducted in such a way that it can be easily understood by the general business audience.
Data Engineer Roles in the Job Market
A data engineer is none other than a person who prepares the data infrastructure for analysis. They are mainly focused on the production readiness of various raw elements and data including resilience, formats, data storage, scaling, and security. As a data engineer, you will also be asked to fulfill the roles of designing, building, testing, integrating, managing, and optimizing data from a large number of sources. They also build the infrastructure and architectures that enable various data generations.
Their main focus however will be on how to build free-flowing data pipelines by using a variety of big data technologies that ensure there is a smooth flow to real-time analytics. Data engineers also write complex queries to ensure the data is easily accessible.
Education and Requirements
Many data scientists and data engineers tend to hold a bachelor’s degree in computer science or a related field which includes mathematics, statistics, information technology, or economics. And while this is exactly what employers are often looking out for you still need to know what are the possible requirements you need before you get to become a data scientist or a data engineer.
What Are the Requirements To Become a Data Scientist?
When you become a data scientist you will often be presented with large amounts of data without having any particular business problems that you need to solve. In such cases, you will have to explore the data, ask the right questions, get your answers, and present them to the stakeholders. This hence makes it essential for them to have quite a broad knowledge regarding various big data infrastructures, machine learning algorithms, data mining, and statistics.
As a data scientist, you also need to work with various data sets in order to run their algorithms efficiently you will need to keep yourself updated regarding all the latest technologies.
Apart from the latest innovations being known to you, you would also be expected to be proficient in various programming languages such as follows:
- Python
- Java
- SQL
You also need to be quite experienced with tools such as MongoDB, Cassandra, Hadoop, and Hive.
What are the Requirements to Become a Data Engineer?
The majority of data engineers have backgrounds in software engineering, which equips them with skills in Python, Scala, and SQL. Alternatively, they might also have a degree in statistics or mathematics which helps apply various analytical approaches which in turn can help solve business problems.
To get hired as a data engineer you will have to have completed a bachelor’s degree in either information technology, applied math, or computer science. Candidates will also be required to get a few certifications which mainly include IBM-certified data engineer or Google’s professional data engineer certification. It will also help greatly if you are experienced in building big data warehouses that can run some Transform, Extract, and Load or ETL on top of big data sets.
Exploring Data Engineering and Data Science in the Job Market
The job market has a place for every role no matter whether you go for data science data engineering. However, you need to explore the landscape before trying to pursue a career in either of them. To understand the same here’s a brief description of how the job market currently looks like.
How much do you earn as a Data Engineer?
You earn around USD 142,000 per year on an average as a data engineer.
How much do you earn as a Data Scientist?
You earn around USD 139,000 per year on an average as a data scientist.
Both of these salary ranges definitely will depend on various factors such as experience carried by the person, the role which pertains, and where the job is located.
When it comes to career path there is no set path. Instead, most of the kids eventually try to navigate through their dreams and reach their desired career path.
How do you determine your career path as a Data engineer?
As a data engineer, you do not usually get an entry-level role. Due to this a lot of data engineers tend to start their careers as a software engineer or in the field of business intelligence and systems analytics. This exposure eventually helps them to open up to new systems and infrastructures that are very important in the field of data science.
How do you determine your career path as a Data Scientist?
Many data scientists when in comparison with data engineers tend to get a lot of entry-level roles. These roles eventually dictate their skills which are being developed. They also design their own experiments and are more involved in solving a lot of business problems.
Can a Data Engineer Become a Data Scientist (or Vice Versa)?
Do you want the shortest answer? Well, then that would be a yes. However, it will definitely need some additional skills to get from one field to another. The overlap in skills can range from knowledge of programming languages to even working with various data pipelines. This eventually will mean that no matter which one you select you will eventually have the basic knowledge and vocabulary that you need for a smooth career transition. Given that data engineers will have a much more focused idea on the architecture of data that helps data scientists, whereas data scientists will have a better view on how to develop these data, both professions will need a lot of skill brush up before making the leap.
What is best for you?
Despite there being an overlap in skills between the two professions including data scientist and data engineers there are certainly varied roles and responsibilities which may be based on the individual personality traits.
You need to consider becoming a data engineer if you love handling the architecture and infrastructure of data. You also need to be a strong coder where you have leverage of new technologies and enjoy discovering new ways in which you can make software and systems more efficient. If you are a thinker who loves to develop new ways to improve the things you build then you definitely need to get into data engineering.
You might want to consider becoming a data scientist if you are an analytical thinker are quite curious and aren’t afraid of putting forth questions. Sounds like something you’d do? Then data science is the profession you need to go for. You need to be able to use data to make sense of stuff that has happened in the past and also forecast things that might occur in the future.
Conclusion
What next? You might now be thinking of choosing from the options placed in front of you that is data engineering vs data science. What to do in such a situation? Well, you need to analyze your personality traits and skills that you consist of and choose one of the professions. If you still think that one of them is not for you then you can always switch to the other one at your own convenience.
FAQs (Frequently Asked Questions)
- Can a Data Scientist work as a Data Engineer and vice versa?
Yes, it is quite easy to even switch between the two professions just that you will need to know certain skills that are essential based on the role you are going for.
- What are the most important skills for a Data Engineer?
SQL is the most fundamental and most important skill set that a data engineer must consist of.
- How do I decide which path is right for me?
You need to look after certain points to be sure which path is the best for you and can include the following points:
- Creation of long-term plans
- Reviewing your work experience
- Being aware of your personality and skills
- Which is harder data engineer or data scientist?
Both of these fields are challenging in their own ways. While data scientists deal with ML algorithms there are data engineers who need to handle data processing and infrastructure.
- Who earns more data scientist or data engineer?
Based on the average salary range, a data engineer surely earns more than a data scientist. However, experience and job location will highly play a role in the determination of salaries.