In the age of information, data-related careers are in high demand. Data architects and data engineers are among the most sought-after jobs in the contemporary era.
So what are the differences between data architects and data engineers? Although they are interrelated and can be used interchangeably, it is very important to understand the fundamental differences in choosing your study.
This post will discuss the core differences between the two professions and help you pick the most suitable career path for your skills and preferences. Continue reading, and I’ll show you.
Data architecture is a branch of IT professionals. A data architect defines the policies, technologies, models, and procedures relating to the information of the company.
These policies and policies identified will be used to collect, organize, access, and store the information more effectively. Unlike data engineers or database architecture, data architects are the bridge between data policies and business intelligence.
In other words, data architects help connect the IT department with the business operations. While IT gathers and stores that information, business operations collect and utilize the data gathered.
Data engineers’ main roles are to design and develop the systems used for collecting, analyzing, and storing data at scale. These systems also help gather and convert the information for the data scientists to analyze and use.
In other words, data engineers make the information become more accessible for other people and organizations can interpret and utilize. This professional plays a vital role in the success of businesses and companies.
Working as a data engineer, you will help the data scientists, decision-makers, and analysts access the information easier.
Before we move on to discuss the core differences in detail, here is a short summary of the differences between the two professions.
|Data Architect||Data Engineer|
|Responsibility||Conceptualizing and virtualizing the data frameworks.|
Instructing and leading the Data Science team.
|Developing, building, and maintaining the data frameworks.|
Providing the Data Science team with the framework and more accessible information.
|Technical skills||Deep expertise and knowledge of databases, data architecture, data modeling, and operating systems.||Great skills and background in application development, coding, engineering, and algorithms.|
|Focus||The main focus is business leadership and high-level data intelligence||The main focus is preparing, analyzing, and converting the data for the other data interpreters to use|
Data architects’ responsibility is to ensure that the company’s departments can access and understand the collected database. In other words, data architects are data engineers, but they have more expertise and experience.
In other words, data engineers cover nearly all the responsibilities of the data-relating professions. They work closely with database administrators, business analysts, application developers, and also data engineers.
Meanwhile, the data engineers can work flexibly in many parts of the data projects, from designing the frameworks to utilizing the data warehouse. Data engineers perform tasks like collecting and cleansing the database.
However, the focus of data architects nowadays is designing and virtualizing the data pipelines to store, interpret and update the database more efficiently.
- The process of interpreting the business requirements to facilitate data collection and usage.
- The principles and concepts of translating and converting business processes to IT applications.
- How the businesses and companies operate, their plans, and changes in the future operation, goals, and practices.
- The function and basics of many database models.
Data architects also have to possess some specific technical skills such as database structure, management, operating the system, and mastering the programming languages.
Meanwhile, you can earn a job in data engineering with an undergraduate degree in math, science, and business. As long as you have the required technical skills and knowledge for data engineering like coding or computing skills.
Here are some in-depth skills you need to develop to become a data engineer:
- Coding: Mastering the programming languages like NoSQL, SQL, Java, R, Python, and Scala.
- ETL systems: These systems include extracting, transforming, and loading the databases from multiple sources into a repository (data warehouse). Some prevalent ETL systems are Stitch, Xplenty, Talend, and Alooma.
- The expertise in data storage, machine learning, cloud computing, and utilizing big data tools is a major advantage for data engineers.
Also, the two professions require some non-technical skills such as critical thinking, communicating, and presenting skills.
According to research, an average data engineer earns $120,813 per year, while the figure for a data architect is $139,946 per year. The salary can vary much more depending on your productivity, skills, and efficiency in the job.
For more in-depth comparisons, consider watching the video below.
The two professions are still evolving and will be in high demand in the upcoming years. They are both suitable for people who love managing and dealing with databases and systems.
Furthermore, data architecture requires deep experience working in the data field, which takes many years to accumulate.
So it is easier to enter the field as a data engineer to obtain the needed skills and knowledge before becoming a data architect if you prefer. If you have the skills needed, starting as a data engineer first is recommended.
To sum up, data architecture demands more experience, knowledge, and skills than data engineering. They work mainly with the business operators and leaders of the companies and organizations.
Think of data architects as the data leader who deals with macro things like strategies and provide the guidelines for other professions like data engineers or data analysis.
I hope that the information in this post can help you understand the basics of the two careers. Thank you for reading!