There is a lot of confusion surrounding the roles of Data Architect vs. Data Engineer. Many people think that they are the same job, but this is not the case.

Data careers are becoming increasingly important and popular all across the globe, simply because “data” is the new currency of the data economy. The pandemic gave the needed push to accelerate the digital transformation of global businesses, and currently, the primary market differentiator is an enterprise’s data infrastructure readiness.

This data infrastructure comprises systems, processes, tools, and qualified manpower. In today’s market, both the data architect and data engineer are more in demand than the data scientist.

Due to the Data Revolution, every company wants to become a data-driven company and they are investing in building their data infrastructure. Data is being generated at an unprecedented rate and it needs to be collected, stored, processed, and analyzed efficiently. Data Architects design this data infrastructure while Data Engineers build it.

But, there’s more to it than that. We’ll break down the Data Architect vs Data Engineer roles in more detail below.

Data Architect vs. Data Engineer

Both jobs are equally essential, but they have fundamental differences. And hiring managers are on the lookout for suitable talent to fill such roles. But you must first distinguish between a Data Architect and a Data Engineer before you start recruiting. This will avoid any confusion later on.

What is a Data Architect?

A Data Architect is someone who designs, creates, maintains, and improves an organization’s data architecture. Data Architects work with Data Engineers to implement the design. Data Architects are also responsible for developing policies and procedures to ensure that data is consistently managed throughout the enterprise.

What are the Data Architect’s Responsibilities

The primary responsibilities of Data Architects are as follows:

• Designing data models and databases – They design data models, database structures, and schemas to ensure that data is properly stored and accessed. Data Architects also design data warehouses, marts, and lakes.
• Developing policies for data governance – They develop policies and procedures to ensure that data is consistently managed throughout the enterprise. Data Architects also create standards for how data should be collected, processed, and stored.
• Creating data architecture diagrams – They create visual representations of an organization’s data architecture. Data Architects use these diagrams to communicate their designs to Data Engineers and other stakeholders.
• Identifying data sources – They identify and evaluate internal and external data sources. Data Architects also assess the quality of these data sources and determine how they can be used to support business goals.
• Optimizing data architecture –They continually optimize the organization’s data architecture to ensure that it meets the changing needs of the business. Data Architects also work with Data Engineers to implement changes to the data architecture.

What Skills Do Data Architects Need To Have?

Data Architects need to have a strong understanding of database design principles. They should also be experts in data modeling and warehousing. Data Architects must be able to use various tools and technologies to design and implement their designs. In addition, Data Architects need excellent communication skills to be able to effectively communicate their designs to Data Engineers and other stakeholders.

Examples of skills a Data Architect might have:

• Data modeling –Data architects should have a strong understanding of data modeling techniques. They should be able to design both relational and NoSQL databases. Data architects should also be familiar with dimensional modeling.
• Data warehousing – Data architects should have a strong understanding of data warehousing concepts. They should be able to design and implement data warehouses. Data Architects should also be familiar with ETL processes.

What’s The Salary of a Data Architect?

As of August 29, 2022, the average Big Data Architect pay in the United States is $157,243 per year, with a range of between $142,324 and $173,538. Salaries can differ significantly depending on a variety of factors such as education level, certifications held and other skills possessed.

Data Architects with more experience can expect to earn higher salaries than those with less experience. Data Architects who have obtained certifications can also expect to earn higher salaries than those who have not. Source: Salary.com

What is a Data Engineer?

A Data Engineer is someone who builds and maintains an organization’s data infrastructure. Data Engineer work with Data Architects to implement the design. Data Engineers are responsible for developing processes and tools to efficiently collect, store, process, and analyze data.

Data Engineer Responsibilities

The responsibility of a data engineer are as follows:

• Designing and implementing data processing systems – Data Engineers design and implement systems to efficiently collect, store, process, and analyze data. Data Engineers also develop processes and tools to automate the data processing pipeline.
• Building and maintaining data warehouses – Data Engineers build and maintain data warehouses. Data Engineers also design and implement ETL processes to load data into the data warehouse.
• Designing and implementing data security measures – Data Engineers design and implement measures to protect an organization’s data. Data Engineers also develop policies and procedures to ensure that data is consistently managed and secured.
• Optimizing data processing systems – Data Engineers continually optimize the organization’s data processing systems to ensure that they meet the changing needs of the business. Data Engineers also work with Data Architects to implement changes to the data architecture.

What Skills Do Data Engineers Need To Have?

Being a data engineer requires knowledge in both software engineering and data science. Data engineering heavily relies on programming, so most professionals who work in this field started their careers as software engineers before pivoting to data engineering.

Examples of skills a Data Engineer might have:

• Database Systems & SQL Language – Data engineers need to be familiar with different types of database systems. Data engineers should have a strong grasp of SQL language. Data engineers should also be familiar with NoSQL database systems such as MongoDB and Cassandra.
• Data Migration and Integration – Data engineers need to be able to migrate data from one database system to another. Data engineers should also be able to integrate data from multiple sources.
• Data Processing Systems – Data engineers need to have a strong understanding of distributed systems. Data engineers should be able to design and implement data processing systems. Data engineers should also be familiar with big data processing frameworks such as Hadoop and Spark.
• Data Security – Data engineers need to be familiar with data security concepts. Data engineers should be able to design and implement security measures to protect an organization’s data. Data engineers should also be familiar with encryption technologies.

What’s The Salary of a Data Engineer?

The average Data Engineer pay in the United States is $111,883 as of 2018, however, the typical salary range is between $96,807 and $128,082.

Salary ranges can vary widely depending on many important factors, including education, certifications, additional skills, and the number of years you have spent in your profession. Source: Salary.com

What’s the Difference Between Data Architects vs Data Engineers?

At a high level, Data Architects design the data infrastructure and Data Engineers build it.

Here’s the outlining of the main difference:

1. Data Architects focus on the conceptual design of the data infrastructure while Data Engineers focus on the implementation of the data infrastructure.
2. Data Architects work with Data Scientists to understand the business needs and develop a plan to meet those needs. Data Engineers work with Data Architects to implement the plan.
3. Data Architects are responsible for the logical design of the data infrastructure while Data Engineers are responsible for the physical design of the data infrastructure.
4. Data Architects focus on the big picture while Data Engineers focus on the details.

In conclusion, Data Architects design the data infrastructure while Data Engineers build it. Data Architects are responsible for the logical design of the data infrastructure while Data Engineers are responsible for the physical design of the data infrastructure. Data Architects focus on the big picture while Data Engineers focus on the details.

Both roles are vital to an organization’s success in today’s data-driven economy. Data Architects and Data Engineers work together to ensure that an organization’s data infrastructure meets the changing needs of the business.

One more thing, a Data Scientist is not the same as Data Architect or Data Engineer. Data Scientists analyze data to extract insights while Data Architects design the data infrastructure and Data Engineers build it.

I hope this article helped you understand the difference between Data Architects vs Data Engineers.

Hiring a Data Architect or Data Engineer

If your organization is looking to hire a Data Architect or Data Engineer, it’s important to understand the difference between the two roles.

Hirefuel specializes in Data Science and Data Engineering recruitment. The team at Hirefuel are professional recruiters with years of experience in the Data Science and Data Engineering space. Contact Hirefuel today to discuss your hiring needs.