When hiring data talent; it can be a challenging task for recruiters, especially ones with no technical background. There are many areas of confusion when trying to attract specialist tech talent and the competition for these skilled employees is fiercer than it’s ever been. 

As more and more companies see data as the new crude oil, businesses are requiring more experts to handle this data and the hunt for tech talent continues. With vacancies opening left right and center, recruiters cannot sit and wait for these positions to get filled by themselves. The demand shifts from candidates looking for jobs, to companies looking for employees. 

The need for data specialists is at an all-time high, with an emphasis on experts that can build complex applications. You may hear these experts call themselves engineers, and use it as a general term to umbrella all the types of engineers; however, they are not all the same.

That’s a distinction between a Data Engineer and a Software Engineer. It would be easier to say that Data Engineers handle the data aspect, and Software Engineers handle the software aspect. 

To differentiate between a Data Engineer and Software Engineer, you need to understand the difference between their roles and responsibilities. 

Table of Content

• Data Engineers

• Software Engineers

• Big Differences Between a Data Engineer and a Software Engineer

• Data Engineer vs Software Engineer Salary

• Staffing: Data Engineers vs Software Engineers

• Summary of the difference between a Data Engineer and a Software Engineer

Data Engineers

Tech Recruiters speak with Data Engineers nearly every day, however, some have little understanding of what they actually do.  

Data Engineering is a part of Data Science. Data Scientists care about exploring data and building machine learning algorithms. Whilst Data Engineers care about making these algorithms work effectively in production infrastructure and creating data pipelines. 

Data Engineers are responsible for setting up and maintaining the organization’s data infrastructure. This infrastructure will store the business’s critical information, ranging from small databases to large-scale systems. The aim is to ensure that the foundation for the data is solid so that critical analyses can be performed and produce reports. 

Responsibilities of a Data Engineer:

Data Engineers will be responsible for managing and organizing data, whilst monitoring any activity that could impact the business. Common responsibilities include:

• Finding hidden patterns within the data
• Data acquisition
• Developing, building, testing, and maintaining architectures that are in line with the business requirements
• Improving the data accuracy, efficiency, and quality
• Perform predictive and prescriptive modeling
• Implementing analytical tools, machine learning, and statistical methods
• Communicate finding with stakeholders

Skills of a Data Engineer:

For Data Engineers to succeed in their role and responsibilities, they need to have specific hard (technical) skills:

• Proficient in one or more programming languages, such as Python, R, and SQL. 
• Understanding of various libraries and frameworks, such as Pandas, NumPy, and Matplotlib.
• Experience with ETL
• Data Warehouse: storing and analyzing volumes of data
• Database system: Understanding of database systems, such as SQL, NoSQL, and Apache Spark systems.
• Business intelligence
• Knowledge of Operating systems, such as macOS, Linux, etc
• Understanding Machine Learning 

Skills of a Data Engineer:

For Data Engineers to succeed in their role and responsibilities, they need to have specific hard (technical) skills:

• Proficient in one or more programming languages, such as Python, R, and SQL. 
• Understanding of various libraries and frameworks, such as Pandas, NumPy, and Matplotlib.
• Experience with ETL
• Data Warehouse: storing and analyzing volumes of data
• Database system: Understanding of database systems, such as SQL, NoSQL, and Apache Spark systems.
• Business intelligence
• Knowledge of Operating systems, such as macOS, Linux, etc
• Understanding Machine Learning 

With the responsibility and skill level of a Data Engineer, they are often considered a jack of all trades. They help with the nitty-gritty tasks that require a lot of trial and error.

Data Engineers need to use their skillset and experience to carefully choose new strategies that can be implemented into their current process. With the constant developments in technology, Data Engineers need to keep up to date with new and upcoming trends. 

When applying for a Data Engineer role; checking the requirements, role and day-to-day tasks will help you understand if this role is for you. If there are some roles you are not familiar with, Staffing companies can help communicate this with the recruiter to get a better insight. This will help not only you but also the recruiter differentiate between a Data Engineer and a Software Engineers role. 

Software Engineers

Software Engineers work with designers, programmers, and other developers to build applications and systems. Their roles include developing operating systems, designing software, front, and back-end development, and developing mobile apps.

Responsibilities of a Software Engineer:

Software Engineers can write the code for applications, websites, and small/large software. Work together with other Software Engineers to test the solutions, and address any problems that may arise. Common responsibilities include:

• Analyzing user requirements
• Be able to write and test code. 
• Be able to research, design, and write new software programs and operating systems
• Be able to evaluate current and new software and systems, develop areas for modification
• Manage software products, and integrate new ones that are compatible with the existing ones.

Skills of a Software Engineer:

To succeed as a Software Engineer, you need to be proficient in the following hard (technical) skills:

• Proficient in one or more programming languages, such as Python, Ruby, and C#.
• Understanding of Object-oriented design process to design a computing system or application.
• Knowledge of Operating systems such as Linux, etc
• Knowledge of UI Toolkits and Frameworks
• Research skills
• Understanding of computer architecture, operating systems, and data structures

Types of Software Engineers

Software Engineering can be broken down into two primary categories:

• Applications Software Engineers

These Software Engineers are responsible for building internal and/or external systems and applications that users can interact with. 

• Systems Software Engineers

These types of Software Engineers are responsible for building and maintaining the organization’s computer systems. 

Front-end and Back-end development in Software Engineers

An important aspect of engineering is front-end and back-end development. Front-end development is also known as client-side development. They are proficient in HTML, CSS, and JavaScript to build websites and applications to improve user interaction. 

Back-end developers are also proficient in HTML, CSS, and JavaScript but they also need to know languages such as PHP, Ruby on Rails, Python, and .Net. They deal with the maintenance of the server-side of an application, from the database and the browser that delivers information to the user.

Applications Software Engineers are primarily involved in both front-end and back-end development, whereas Systems Software Engineers are primarily involved in back-end development. 

Big Differences Between a Data Engineer and a Software Engineer

As we have gone through the roles and skills of both a Data Engineer and a Software Engineer. It is difficult to distinguish between the two as the roles and skills look very similar. 

Below are the differences between the two and how staffing companies can help applicants better understand what the role entails through these big differences. 

Similar knowledge, different applications

Data Engineers and Software Engineers have similar skills, however, the difference is how they apply their knowledge.

For example, Data Engineers can be responsible for building and testing a model, however that model needs to run effectively inside a software application. This is where Software Engineers come into play; as they have the skill to build these platforms.

Understanding where you will be applying your knowledge is important during the recruitment process. You don’t want to apply to a job to find out that your skills cannot be applied the way you wish. 

 Task type

The difference between the two roles is also dependent on the scale of work they do. 

Software Engineers normally deal with developing large-scale systems, platforms, and applications. Their knowledge of both front-end and back-end allows them to deal with more complex tasks than Data Engineers. 

However, Data Engineers can work on the smaller complex tasks, that help build up to the bigger ones. Data engineers are well versed in dealing with data warehouses, which is one of the weak points of Software Engineers. 

Detailing out the type of task makes the recruitment process smoother for both the applicant, recruiter, and company. 

Problem-Solving

Data Engineers deal with the nitty-gritty tasks, they apply their knowledge to each individual task. 

Software Engineers apply their logic in the applications, where all the logic exists. This reduces the need to go back and add extra logic which increases the complexity and future testing in the data pipeline.

Stating the type of problem solver a company needs will help applicants understand if the company needs a Data Engineer or a Software Engineer. IT Staffing companies have a better understanding of the two and can help an applicant’s recruitment process be more smooth by guiding them to apply for the right job. 

Data Engineer vs Software Engineer Salary

Due to the level of responsibilities between the two, there is a difference in the salary. According to Indeed, the average base salary for a Data Engineer is $124,748, whereas the average base salary for a Software Engineer is $125,742.

However, these salaries are dependent on different factors, such as location, company, or experience. For example, big locations such as San Fransisco, London, and Singapore have a high demand for these opportunities, which would reflect the salary increase. Staffing companies can negotiate a better salary based on the applicant’s skills and knowledge. 

Staffing: Data Engineers vs Software Engineers

It can be challenging for any organization to determine whether they need a Data Engineer or a Software Engineer. With the similarities between the two, many people apply for jobs as a Data Engineer but realize that they are getting vetted for a Software Engineer position. 

It is important for recruiters to understand the intricacies of the job role by speaking with the managers in the data team. This is a key element for a recruiter to help their process and find their gold candidate.

It can be frustrating for anybody to be going through an interview process to find out they got the obligations of the role mistaken. This can prevent a lot of wasted time and resources.

Although these roles have similar skills; outlining what the candidate’s day-to-day tasks involve will help them understand if the role is for them and if they have experience in the area.

Summary of the difference between a Data Engineer and a Software Engineer: