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, which describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and purge data. They have a holistic vision of the company’s data architecture, which describes the structure of an organization’s logical and physical data assets and data management resources.

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

Data architect responsibilities

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 the data flows, or which parts of the organization generate data, that 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. Armando Vázquez, data architect at Popular Bank, identifies nine common types of data architects:

Enterprise data architects oversee an organization’s overall data architecture, define data architecture strategy, and design and implement architectures.
ML architects design scalable systems for use with ML and AI models.
Solutions data architects design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes.
Application data architects design and implement data models for specific software applications.
Information/data governance architects establish and enforce data governance policies and procedures.
Analytics/data science architects design and implement data architecture that supports advanced analytics and data science applications, including ML and AI.
Cloud data architects design and implement data architecture for cloud-based platforms such as AWS, Azure, and Google Cloud Platform.
Data security architects work closely with security teams and IT teams to design data security architectures.
Big data architects design and implement data architectures supporting the storage, processing, and analysis of large volumes of data.

Data architect vs. data engineer

Data architect and data engineer roles are closely related. In some ways, the data architect is an advanced data engineer but they 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, a producer of educational data management resources for business and IT professionals, 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.

Data architect vs. data scientist

The data architect and data scientist roles are related, adds Dataversity, but data architects focus on translating business requirements into technology requirements, defining data standards and principles, and building the model-development frameworks for data scientists to use. Data scientists are experts in applying computer science, mathematics, and statistics to build models.

How to become a data architect

Data architect is an evolving role and there’s no industry-standard certification or training program for data architects. Typically, data architects learn on the job as data engineers, data scientists, or solutions architects, and work their way to data architect with years of experience in data design, data management, and data storage work. Prospective data architects should seek experience in data modeling, data warehousing, database management, and ETL.

What to look for in a data architect

Most data architects hold degrees in IT, computer science, computer engineering, or related fields, and have a solid understanding of the cloud, databases, and the applications and programs used by those databases. They understand data modeling, including conceptualization and database optimization, and demonstrate a commitment to continuing education.

Data architects have the ability to:

design models of data processing that implement the intended business model.
develop diagrams representing key data entities and their relationships.
generate a list of components needed to build the designed system.
communicate clearly, simply, and effectively.

What are the daily duties of a data architect?

According to online course provider Coursera, the day-to-day responsibilities of data architects include:

translating business requirements into databases, data warehouses, and data streams.
creating procedures to ensure data accuracy and accessibility.
analyzing, planning, and defining the data architecture framework, including security, reference data, metadata, and master data.
creating and implementing data management processes and procedures.
collaborating with other teams within the organization to create and implement data strategies, build models, and assess shareholder needs and goals.
researching data acquisition opportunities.
developing APIs to retrieve data.

Data architect skills

Data architects require math and computer science proficiency, data management skills, and the ability to analyze and present statistical information.

According to job search portal Teal, important data architect skills include:

data modeling and design. Data architects must have the ability to design comprehensive data models that reflect complex business scenarios. They must be proficient in conceptual, logical, and physical model creation, which often includes SQL development and database administration.
data governance and compliance. With regulations constantly evolving, data architects must ensure their organization’s data management practices meet stringent legal and ethical standards. They need skills to create frameworks that maintain data quality, security, and privacy.
cloud computing expertise. With organizations continuing to migrate to cloud-based solutions, understanding cloud services, architectures, and storage solutions is essential, as well as cloud security, hybrid cloud environments, and cost-efficient infrastructure design.
proficiency with big data technologies. Data architects must know how to implement big data solutions to stream data and real-time analytics.
ML and AI integration. They must understand how to build data pipelines that feed into AI algorithms and how to structure databases for ML workloads.
interdisciplinary collaboration. Data architects have to work closely with stakeholders including business leaders, IT professionals, data scientists, and developers. They also have to translate business requirements into technical specifications, and vice versa.
continuous learning and adaptation. Data architects need to understand established data management and reporting technologies, and have some knowledge of columnar and NoSQL databases, predictive analytics, data visualization, and unstructured data.

Other important skills include:

having a foundation in systems development. Data architects should understand the system development life cycle, project management approaches, and requirement, design, and test techniques.
being a strong communicator and politically savvy. Data architects need people skills, and be articulate, persuasive, and good salespeople, and know how to conceive and portray the big data picture to others.

Data architect certifications

Despite no industry-standard certifications for data architects, there are some certifications that may help data architects in their careers. In addition to certifications in the primary data platforms used by their organization, the following certifications are popular:

For more information about certs, click here.

Data architect salary

According to compensation analysis from PayScale, the median annual data architect salary is $136,000, with total pay, including bonuses and profit share, ranging from $87,000 to $198,000. Data architects in Los Angeles earn an average of 15.6% more than the national average, while in Washington, DC, and New York City, data architects earn 13.1% more and 10.4% more, respectively, than the national average.

Here are some other popular job titles related to data architecture and the average salary for each position, according to PayScale:

BI architect: $85,000-$164,000
Data engineer: $71,000-$142,000
Data warehouse architect: $84,000-$200,000
Database architect: $84,000-$185,000
Information architect: $81,000-$168,000
Solutions architect: $87,000-$180,000

Data architect jobs

Indeed.com shows data architect positions available in a range of industries, including consulting, financial services, healthcare, higher education, hospitality, logistics, pharmaceuticals, retail, and technology.

A sampling of data architect job descriptions shows key areas of responsibility such as creating a DataOps and BI transformation roadmap, developing and sustaining a data strategy, implementing and optimizing physical database design, and designing and implementing data migration and integration processes.

Companies look for bachelor degrees in computer science, information science, engineering, or equivalent fields, though master’s degrees are preferred. Most look for eight to 15 years of experience in a related role, and they want highly motivated, experienced innovators with excellent interpersonal skills, strong collaboration, and the ability to communicate effectively, both verbally and in writing.