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As the world consumes more and more data, businesses increasingly require experts who know how to handle large amounts of customer information, competitor research and product performance results. They also need professional developers to build and manage their increasingly complex websites and apps. These two distinct needs have led to two exciting tech fields: data engineering and software engineering. The two sometimes overlap, but actually have different areas of expertise.

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To those outside the tech world, terms like “data engineer” and “software engineer” may sound interchangeable, since both rely heavily on programming skills. Some may even assume that data engineers and software engineers do the same thing.

In reality, software engineers usually only engage in data infrastructure to a limited extent. Their primary focus is on building websites that function well for the end-user. The task of data engineers, however, is to maintain large datasets and build the structures that house them. So while each profession involves a common background of data management, software engineers and data engineers have vastly different responsibilities.

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Here are some of the important differences between data engineers and software engineers.

What’s the Difference between a Data Engineer and a Software Engineer?

Data engineers build systems that can store, consolidate and retrieve data that’s required for the systems and applications built by software engineers. Data engineering emerged as a specific skill from within the software engineering profession, since data engineers are trained to handle tasks independent of the tasks assigned to the software engineering department. Data engineers pull out data from stable, well-documented APIs designed to retrieve historical data from another party. Research shows that around 40% of data engineers previously worked as software engineers.

Data engineers are specialists within the field of software engineering. They are responsible for making accurate data available to end users such as executives, data scientists, or analysts, enabling them to make crucial decisions. The work of a data engineer includes distributed computing, advanced data structures, building data pipelines, and concurrent programming, to name a few. The field is dynamic and data engineers need to update their skills regularly in order to adapt to new tools such as Kafka, Hadoop, Hive, and Spark, if they want to stay competitive.

A software engineer, on the other hand, works with designers, programmers, and developers to build applications and systems. The tasks of a software engineer include the development of the operating systems, software design, front and back-end development, and developing mobile apps.

Software engineers are also sometimes called infrastructure or platform engineers. They are primarily focused on data modeling, SQL, and applying technologies like Spark and AWS. Unlike data engineers who are specialized in their tasks, software engineers function at a higher level. They’re responsible for building the system that imports and stores the data, be it a website, specialized software, or app.

How to Succeed as a Data Engineer

To excel as a data engineer, you need a strong grasp of programming languages, databases, and tools, as well as the ability to collect, query, and store information from databases. The recent growth of Big Data has placed more responsibility on data engineers, who now need to have a keen understanding of legal implications and privacy concerns. To excel in this field, you’ll need to be able to navigate this new territory with confidence.

A data engineer should have excellent working knowledge of Python and SQL and be well versed in Java. Experience working with cloud platforms like Amazon Web Services will add credibility to your profile. A strong understanding of NoSQL and SQL databases will also be essential to those working in data warehousing and data modeling.

How to Succeed as a Software Engineer

Software engineers need to be fast and efficient, as they have to handle macro-level tasks. Apart from the technical aspect of building systems and writing code, software engineers should also be team players and good communicators. As a software engineer, you’ll work with various people including project managers, quality assurance professionals, sales reps, developers, and customers. From a competitive standpoint, you’ll need to stay up to date with developments across your industry .

Difference in Salary between Data Engineers and Software Engineers

There isn’t much difference in the compensation for these two roles, although data engineers net a slightly higher salary. An aspiring data engineer typically pursues a bachelor’s degree in computer science or computer engineering, as well as a knowledge of applied mathematics, statistics, or physics. Beyond this, they need to take courses on database management, algorithms, data structures, and coding. According to reports, data engineers in 2018 earned around $118,370, which was a growth of 16% above the previous year.

A software engineer may have a bachelor’s degree in computer science, although it’s not required to excel in the field. As previously mentioned, software engineers work at a macro level, requiring analytical engagement, teamwork, problem-solving, and communication skills. In 2018, a typical software engineer earned a median annual salary of $105,590.

How to Start Your Career in Data Engineering

If you’ve got your heart set on becoming a data engineer, you might start with a bachelors degree (although it’s not necessarily required to land a job). You should also be prepared to use certain programming languages for data mining, like SQL.

If you can demonstrate your ability to deftly pull insights from large datasets, then you’ll get hired in an entry-level data engineering job. After about a year of experience, you could increase your earning potential with a master’s degree, or throw your hat in the ring for a more senior position. Some also consider getting certified in big data, although many employers actually favor relevant data analysis skills and experience rather than a certification.

Throughout your career as a data engineer, take every opportunity to collaborate with interdisciplinary groups like data modelers, architects, and other IT specialists to draw knowledge from their projects and use it to improve your own approach.

How to Start Your Career in Software Engineering

Software engineers have a broad knowledge base beyond code. Depending on the specific needs of the company, a software engineer might specialize in databases, middleware, network control systems, or business applications. If any of these responsibilities catch your attention early on, then focus on honing your skill set and establishing yourself in that niche of engineering.

To become a software engineer, some choose to pursue a bachelors degree in a related field like computer science. You might also apply for an internship to gain hands-on, practical experience. There’s also an array of professional certifications that promise to help you get hired as a software engineer.

While all of these approaches are perfectly effective when it comes to starting your career, a coding bootcamp can help you learn the exact skills you need in less time, and at a lower cost. You’ll create a portfolio of work that demonstrates your front-end and back-end coding skills, while building industry connections and partnering with an experienced mentor. All of these factors could result in a high-paying software engineering gig.

Data Engineering vs Software Engineering: Similar Skills, Different Professions

In short, data engineers examine the practical applications of data collection and help in the process of analysis. Data engineers work closely with large datasets, and build the structures that house that data long-term. Data engineers should be well versed in programming languages like SQL that allow them to build, maintain and secure big data. Most data engineers have been software engineers at some time in their career and have moved on to specializing in data engineering.

Software engineers are also skilled in computer programming, but they perform work that includes designing and developing operating systems, as well as front and back-end development. While some software engineers rely heavily on data, you’re not guaranteed to focus on data analysis if you pursue a career in engineering. Engineers who focus on front-end web development, for example, are much more concerned with the look and feel of a website, rather than organizing the data on the back end.

If you’re interested in learning more about software engineering, data engineering and data science, our tech careers blog covers everything you need to know about breaking into these exciting new fields.

We’ve explored what it’s like to work as a full-time developer, created valuable cheat sheets to serve you throughout your career development, and researched the most sought-after tech skills. You can get hired as a full-time software engineer, data engineer, or any other tech professional - even if you don’t have a degree. You just need to know where to start.

When you’re ready to take the next step, try an online software engineering course to learn the skills you need, and launch your tech career.

Which Tech Career is Right for You?

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Career in Software Engineering

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Beginner's Guide

Getting a Software Engineering Job

Software engineering is a smart career choice – it’s one of the most in-demand skills in the world and American software engineers earn a median salary of $112,000.

But all software engineers aren’t created equal and there are cities in America that pay software engineers significantly more than others. Using data from our friends at LinkedIn Talent Solutions, we identified the the highest-paying types of software engineers and the American cities that pay them the most; along with what activities software engineers tend to do more of than other professionals.

1. Software engineers can be roughly grouped into six specialties.

After examining millions of LinkedIn profiles of software engineers, we found that most engineers fit into six areas, such as front-end and mobile.

Front-End Engineers: By far the biggest talent pool, their population is more than double that of the second-biggest specialty.

Embedded and Application Engineers: These engineers focus primarily on the IoT and are one of the smallest talent pools, but also the most experienced. It’s also the least gender-diverse.

Infrastructure and Cloud Computing Engineers: They tend to be more experienced. Like embedded and application engineers, 77 percent of infrastructure and cloud professionals have more than 10 years of experience.

Machine Learning and Data Science Engineers: The smallest specialty – and the most in-demand (more on that in the next section). This is a good place to be.

Mobile Engineers: The second-biggest specialty, and they’re also the youngest cohort – 37 percent of these engineers have less than 10 years of experience, more than any other specialty.

Test and Quality Assurance Engineers: The most gender-diverse group – and yet even there, women represent only around 30 percent of its talent pool. It’s worth noting that, based on this demographic data, all specialties have a long way to go until they reach gender parity.

2. Software engineers who specialize in machine learning and data science are the most sought-after.

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Software engineers get three-times as many InMails from recruiters on LinkedIn as the average professional. But certain specialties tend to draw even more interest, meaning it’s even easier to get a job.

Here is how the supply of software engineering talent stacks up relative to demand from organizations, by the six specialities:

A few takeaways:

There’s the most demand for software engineers who specialize in machine learning and data science, and yet there is also the least supply. That means software engineers with that speciality are often swimming in opportunity.
Test and quality assurance specialists are the only engineers where the supply outstrips the demand, albeit barely. Relax – it’s still a good career choice; it’s just not as in-demand as other specialities.
Engineers who specialize in infrastructure and cloud are low in relative supply and demand. But all signs suggest demand is about to vastly increase – tech experts agree that cloud engineering is a must-have skill for technologists moving forward.

3. They are also the highest paid.

Unsurprisingly, thanks to large demand and short supply, software engineers who specialize in machine learning and data science are the highest paid.

The good news? The lowest specialty on the list – test and quality assurance – still has a median salary of $103,000 a year. Not bad.

4. San Francisco pays software engineers the most; Detroit, the least.

For software engineers, geography has a tremendous effect on their paychecks. In the San Francisco Bay Area, software engineers make a median salary of $142,000 – in Detroit, they make $88,0000.

Of course, the cost-of-living varies greatly across these regions as well. Consider Seattle – not only is the median salary high at $132,000 annually and the cost-of-living less than the San Francisco area, it’s also the fastest growing area in the country for software engineers.