Software engineer vs. data engineer. People outside these professions are often confused about the differences between these experts. They may think these are two different names for the same thing: a programming expert. Of course, the duties of each engineer type are different, but their roles are similar enough to confuse people who are in the industry as well.
If you are a new data engineer, you may be confused yourself. What exactly separates you from a software engineer? The answer is not a simple one. In fact, you can honestly say "It depends on the circumstances." While there are tangible differences, the two positions frequently perform some of the same duties.
Since people often ask about the differences between a data engineer and a software engineer, you should have an answer. These are two separate careers, so having a definition should not be difficult, you may think. In reality, discussing the differences is challenging because their duties often overlap. On any given day, you can find a software engineer working with data concepts and a data engineer writing code.
However, this type of overlap is common in many industries, including education. Think about school administrators versus classroom teachers. You wouldn't be shocked to find a principal delivering a lesson or a teacher dealing with discipline issues. But you would understand that the focus of their jobs differs. The principal's focus is on administration issues and the teacher delivers lessons and manages the classroom. Software and data engineers have a different daily focus.
Data engineers are not all the same. In fact, you will find at least two main types of data engineer: A data engineer who is really a software engineer with a data focus and a BI developer type of data engineer.
The former data engineer does more than write code for data pipelines. If you fit this category, you may also develop logging and monitoring systems that manage the data pipelines, tasks that are more on the software engineering side.
If you are the latter data engineer type, you will probably use more Dragon Drop and Airflow coding because others have already developed the infrastructure. Instead, you are often parameterizing data pipelines and completing the tasks they need to run.
Of course, these data engineer categories can also overlap depending on your employer and changing circumstances. Data engineers need to be flexible.
Data engineers and software engineers may not approach their duties in the same way. If you are a data engineer, you probably take a different approach to problem-solving than a software engineer does. Often, you can see these differences in where the engineer places their logic.
Software engineers like to have one place for all logic so they do not have to add extra logic layers downstream. They like things upfront to simplify the process.
In contrast, if you are a data engineer, you probably like to put more logic on the SQL side. This preference has to do with your skill set. A data engineer needs to develop categories in order to map data from different suppliers. You must categorize so you can simplify naming conventions and mapping.
A data engineer will also rely on tables and SQL, while a software engineer will lean on Python, etc. Despite these innate preferences, as a data engineer, you should put your logic upstream as far as possible in order to reduce errors. Adding layers of logic as you go can become needlessly complex and make it vulnerable to problems.
The salary edge usually goes to the software engineer, something that is obviously not popular with you and others in the profession. This difference is most common in larger companies where software engineers may earn as much as 40% more than a data engineer. However, in smaller companies, the salary difference may be smaller since the job duties may overlap more. In reality, they may not care that much about the differences in engineer definitions. Your salary will depend on what you give the company more than what your title is.
Data engineers and software engineers are definitely not the same. The skill sets for data engineers do differ from those of software engineers although some skills are needed in both professions. Companies that rely on SQL may value the data engineer more since you are much stronger in this area. As a data engineer, you have honed your SQL skills since you are continually modeling, structuring, and manipulating data. Software engineers are weaker here since SQL generally doesn't affect their jobs as much. Their focus is usually on functions such as insert, delete, and update which do not require as much in-depth SQL knowledge. You have a definite career advantage in this area.
Some experts try to put a stricter definition on software engineers and data engineers and see fewer overlapping skills. They may base their conclusions on what coding languages each engineer type uses and on other criteria that really do not hold up. For instance, while software engineers might use C# more often, data engineers certainly use it in their duties, too. There is no point in creating artificial boundaries between the two careers. The job definitions should be based on reality and not theory.
The duties of data engineers and software engineers overlap, especially in smaller companies. But there are tangible differences between the two. For instance, data engineers generally work with Dragon Drop coding and data visualization. You will probably be coding but not nearly as much as a software engineer.
But as a data engineer, you can lean more toward a software engineer's role and end up doing lots of data pipeline coding. You will not be dealing with many infrastructure and core data layers, however.
You may be a data engineer who focuses on BI work and modeling and not software engineering. In that case, you will be the more traditional data engineer who moves data from point A to point B. You will be concerned with data warehousing, ETLs, ELTs, and data lakes. And with the many advanced software programs out now, you simply will not have to work with as much coding.
In larger companies, data engineers focus on data pipelines, but in smaller businesses, data engineers do more software engineering in order to develop these pipelines. Also, you will often place your logic in code on the SQL side, while software engineers place it far upstream.
In short, your duties as a data engineer vs. software engineer largely depend on your employer.
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