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Data Scientist vs. Data Architect: What Are the Differences?

Learn about the two careers and review some of the similarities and differences between them.

Data scientists and data architects are two important roles in the field of data. Data scientists analyze and interpret data, while data architects design and build data systems. Both positions require strong technical skills, but data scientists also need strong analytical and communication skills. In this article, we compare and contrast these two data roles, and we provide tips for pursuing a career in data.

What is a Data Scientist?

Data Scientists analyze complex data sets to identify trends, patterns and relationships. They use their findings to help organizations make better decisions about everything from product development to marketing campaigns. Data Scientists typically have a background in mathematics, statistics or computer science. They use their technical skills to clean and organize data, then they use their analytical skills to interpret the data and find ways to solve problems. Data Scientists often work with Data Analysts and Data Engineers to help them understand and use the data they’ve collected.

What is a Data Architect?

Data Architects design and oversee the development of an organization’s data infrastructure. This includes developing policies and procedures for data management, as well as designing and implementing systems for storing, retrieving and analyzing data. Data Architects also work with business stakeholders to identify their data needs and ensure that the data infrastructure meets those needs. They may also be responsible for developing data models and ensuring that data is properly integrated across multiple systems. Data Architects typically have a strong background in computer science and experience working with databases and data mining.

Data Scientist vs. Data Architect

Here are the main differences between a data scientist and a data architect.

Job Duties

Data scientists and data architects have different job duties. Data scientists use their knowledge of machine learning, artificial intelligence and data analytics to extract information from large volumes of data. They then analyze the data and develop algorithms that can help business leaders make better decisions. Data architects design databases that meet an organization’s business needs. They ensure that databases are secure and that organizations can easily access the data they need.

Job Requirements

Data scientists and data architects typically need at least a bachelor’s degree in computer science, mathematics or another related field. However, many employers prefer candidates who have a master’s degree or higher. Data scientists and data architects might also pursue certifications to show their proficiency in specific software programs or programming languages. For example, the Oracle Certified Professional (OCP) credential is available for professionals who want to work with the Oracle database management system.

Work Environment

Data scientists and data architects work in different environments. Data scientists typically work for companies or organizations that need to analyze large amounts of data to make decisions about their business. They may also work as consultants, helping clients with specific projects.

Data architects usually work for companies that have a lot of data to manage. They often work for software development firms or technology companies. Some data architects work for government agencies or educational institutions.


Both data scientists and data architects need to have strong analytical skills. Data scientists use their analytical skills to examine data sets, identify trends and develop models that explain the data. Data architects use their analytical skills to design database systems that are efficient and meet the needs of the users.

Both data scientists and data architects need to be proficient in programming. Data scientists use programming languages like R and Python to clean data sets, run statistical analysis and build data models. Data architects use programming languages like SQL to design databases, write code to create tables and indexes, and query data.

Data scientists need to have strong communication skills to present their findings to clients or managers. Data architects need to have strong communication skills to discuss the design of their database systems with clients or managers.

Data scientists benefit from having a background in statistics. Data architects benefit from having a background in computer science.


Data scientists earn an average salary of $118,822 per year, while data architects earn an average salary of $122,954 per year. Both of these salaries can vary depending on the size of the company, the location of the job and the level of experience you have prior to pursuing either position.


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