What is a data architect? Skills, salaries, and how to become a data framework master

Data architect role

Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. The data architect is responsible for visualizing and designing an organization’s enterprise data management framework. This framework describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and purge data.

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

Data architects are frequently part of a data science team and tasked with leading data system projects. They often report to data infrastructure and data science leads.

Data architect responsibilities

According to Panoply, typical data architect responsibilities include:

• Translating business requirements into technical specifications, including data streams, integrations, transformations, databases, and data warehouses
• Defining the data architecture framework, standards, and principles, including modeling, metadata, security, reference data such as product codes and client categories, and master data such as clients, vendors, materials, and employees
• Defining reference architecture, which is a pattern others can follow to create and improve data systems
• Defining data flows, i.e., which parts of the organization generate data, which require data to function, how data flows are managed, and how data changes in transition
• Collaborating and coordinating with multiple departments, stakeholders, partners, and external vendors

What are different types of data architect?

Data architecture is a complex and varied field and different organizations and industries have unique needs when it comes to their data architects. Data architect Armando Vázquez identifies eight common types of data architects:

• Enterprise data architect: These data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.
• Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes.
• Application data architect: The application data architect designs and implements data models for specific software applications.
• Information/data governance architect: These individuals establish and enforce data governance policies and procedures.
• Analytics/data science architect: These data architects design and implement data architecture supporting advanced analytics and data science applications, including machine learning and artificial intelligence.
• Cloud data architect: The cloud data architect designs and implements data architecture for cloud-based platforms such as AWS, Azure, and Google Cloud Platform.
• Data security architect: The data security architect works closely with security teams and IT teams to design data security architectures.
• Big data architect: The big data architect designs and implements data architectures supporting the storage, processing, and analysis of large volumes of data.

Data architect vs. data engineer

The data architect and data engineer roles are closely related. In some ways, the data architect is an advanced data engineer. Data architects and data engineers work together to visualize and build the enterprise data management framework. The data architect is responsible for visualizing the “blueprint” of the complete framework that data engineers then build. According to Dataversity, data architects visualize, design, and prepare data in a framework that can be used by data scientists, data engineers, or data analysts. Data engineers assist data architects in building the working framework for data search and retrieval.