What Are the Core Differences Between a Data Engineer & a Data Architect?

Businesses deal with huge quantities of data to keep everything running smoothly. Offering customer insight, productivity metrics, and a general overview of a company’s relative quarterly success, there’s almost nothing that data cannot achieve. To get the most out of it, businesses employ the distinct roles of data engineers and data architects to manage data and construct pipelines to get it from A-B.

We’re not saying that these two roles are completely different. After all, a knowledge of similar languages like Python, Java, R, and an advanced understanding of SQL will be common to anyone in data, no matter whether they’re an architect or an engineer.

However, just because these two roles share a few skills does not mean that they’re exactly the same. In this article, we’ll break down the two job roles, demonstrating what they do and what their main functions are within business. From there, we’ll outline the core differences to make sure we’re all on the same page.

Let’s jump right into it.

What is a Data Engineer?

Data engineer is an incredibly broad term, as a person with this title could have their specialty in anything from designing and maintaining data pipelines to completing statistical analysis. This is a huge area of knowledge, with the commonality across these different people being that they’re tasked with making sense of data.

In 2022, 2.5 quintillion bytes of data were created every single day. With this mounting tide of data, businesses are starting to get overwhelmed by the sheer quantity that they need to deal with. To help them combat this rising wave, they employ data engineers (in their many forms) to control and manage information.

A data engineer will often have a background in mathematics, statistics, computer science, or computer engineering. As time goes on, skills in big data are becoming even more important for this role.

Here are some common functions that you’d find a data engineer doing on any given day:

• Gathering raw data and processing it
• Creating data frameworks
• Maintaining databases and data pipelines
• Creating data apps and designing them from the ground up.
• Ingesting and storing different types of data

Now that we’ve got that cleared up, let’s move on to data architects.

What is a Data Architect?

Data architects are tasked with constructing the connective pathways that get company data from its storage location into tools and platforms that employees will use to access it. They’re in charge of accessibility, acting as the person that’s between the IT team of a department and the rest of the organization.

Often, a data architect will be given a set of goals or tasks from higher-ups in the business. This could include finding a way to get certain company data into an analytical tool, or developing a new way of presenting information. Their job is to turn these business requirements into technical architecture, designing and creating new data infrastructure as they go.

Most of the time, data architects will work with almost everyone within the IT department. No matter whether it's a data scientist, data analyst, or even data engineers, they have some degree of contact. Due to this, they need advanced knowledge of a number of data fields, covering collection, security, storage, transformation, access, and presentation.

Here are some common functions that you’d find a data architect doing on any given day:

• Work with a business to define business goals and then create technical schematics which can help to achieve them.
• Knowledge of both sides of the data spectrum, from BI presentation and analytics to ETL tools
• Machine learning, data modeling, and database administration experience.
• Understanding of data warehouses and database architecture 

While both a data engineer and a data architect will use languages like Hive, Python, SQL, and noSQL, the latter will also work with visualization tools. Often, data engineers will have at least a Bachelors in a technical field, if not a Masters.

What Are the Core Differences Between These Roles?

Even from these descriptions, you can instantly see that there are a range of differences between data engineers and data architects. For those not actively working in data, the distinctions might seem minute. Yet, the reality is that they are two radically different roles, even being located at entirely different positions in the business framework.

Let’s jump into some of those core differences:

• Position in the Business - Data architects will discuss with with other business teams to decipher what they need to work well. From there, they’ll design plans that the data engineers will then bring to life. Due to this, data architects are normally positioned between the larger data teams and all other business teams, acting as intermediaries.
• Total Compensation - While not technical, these roles are often compensated differently. A data engineer will earn an average of $92,000 per year, while a data architect will pull in a higher figure of $119,000 a year.
• Tools Used - With differing job focuses, the tools and common languages that a data engineer vs a data architect use will be radically different. While both will have an understanding of many of the same areas, they won’t use them to nearly the same extent. For example, both will use python, but a data engineer will make this a primary language, while a data architect would only use it as a secondary or even tertiary language.
• Job Role Focus - Distilling their roles down, data engineers will build frameworks and then maintain them. On the other hand, data architects will design, visualize, and conceptualize the framework that the former builds.

Across these core differences, we’ve outlined just how different these two roles are. Depending on your particular interests and skillsets, one job path may suit you more than another.

Final Thoughts

Both data engineers and data architects are vital in helping businesses get the most out of their data. Without these roles, businesses would have a hard time gaining any semblance of data insight, reducing their hard-earned data into just a bunch of numbers. Each role brings a different skill set to the table.

Although data architects often seem to get a little more credit than data engineers, the reality is that both job roles are absolutely essential. Yes, they offer different things. But, for the most part, what they offer cannot be categorized as more or less important. For a business, it’s always a good idea to have a range of both of these roles in your employee force.