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.
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, and 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 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. Data architect Armando Vázquez identifies nine common types of data architects:
Enterprise data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.
Machine learning (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
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 to visualize 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, says 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 building 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.
What to look for in a data architect
Most data architects hold degrees in information technology, 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 application programming interfaces (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. This is the core skill of the data architect and the most requested skill in data architect job descriptions. This often includes SQL development and database administration.
data governance and compliance. With regulations continuing to evolve, 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. Organizations are continuing to migrate to cloud-based solutions, making understanding of cloud services, architectures, and storage solutions essential. They must also understand cloud security, hybrid cloud environments, and cost-efficient infrastructure design.
proficiency with big data technologies. Data architects must understand 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 must be able 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:
a foundation in systems development. Data architects need to understand the system development life cycle, project management approaches, and requirements, design, and test techniques.
communication and political savvy. Data architects need people skills. They must be articulate, persuasive, and good salespeople, and they must 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:
Certified Data Management Professional (CDMP)
Arcitura Certified Big Data Architect
IBM Certified Solution Architect – Cloud Pak for Data v4.x
Salesforce Certified Data Architect
For more information about certs, see “Top 11 data engineer and data architect certifications.”
Data architect salary
According to compensation analysis from PayScale, the median data architect salary is $133,000 per year, with total pay, including bonuses and profit share, ranging from $86,000 to $192,000 annually. Data architects in New York City earn an average of 22.7% more than the national average. In Washington, DC and Boston, Massachusetts, data architects earn 15.7% more and 12.7% more, respectively, than the national average. The lowest data architect salaries are in Minneapolis, Minnesota, (7.4% less) and Chicago, Illinois (3.7% less).
Here are some other popular job titles related to data architecture and the average salary for each position, according to PayScale:
BI architect: $86,000-$160,000
Data engineer: $69,000-$138,000
Data warehouse architect: $78,000-$154,000
Database architect: $85,000-$181,000
Information architect: $75,000-$162,000
Solutions architect: $82,000-$174,000
Data architect jobs
A recent search for data architect jobs on Indeed.com showed 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 are looking for bachelor degrees in computer science, information science, engineering, or equivalent fields, though master’s degrees are preferred. Most are looking for 8 to 15 years of experience in a related role. They want highly motivated, experienced innovators with excellent interpersonal skills, strong collaboration, and the ability to communicate effectively, both verbally and in writing.
The need for data architects
Data architects are in strong demand. The US Bureau of Labor Statistics says there were 141,900 data architect jobs in the US in 2023, and projects the number of data architects will grow by 9% from 2023 to 2033, which is faster than average for all other occupations in the US.
More on data architecture and science:
What is data architecture? A framework for managing data
The top 8 data engineer and data architect certifications
Essential skills and traits of elite data scientists