Like traditional architects, data architects design the blueprints organizations use for their data management systems.
Leer en español. (Read in Spanish.)
Much like traditional architects draw up blueprints for the framework used to create structures, data architects design the blueprints that organizations use for their data management systems. This includes drafting a data management framework to meet business and technology requirements while ensuring data security and compliance with regulations. Data architects work in a variety of industries, including the technology sector, entertainment, health care, finance, and government.
Interested in launching your career in data architecture? Learn how to get started in this guide.
Data architects are IT professionals who leverage their computer science and design skills to review and analyze the data infrastructure of an organization, plan future databases, and implement solutions to store and manage data for organizations and their users.
Since almost every company uses data, data architects can work in nearly any industry, including technology, entertainment, health care, finance, and government.
While closely related, the two professions are not the same. Data architects design and manage database systems architecture, including the ways people access and interact with their data. Data engineers create and manage data pipelines, finding ways to most effectively process and analyze large data sets, design machine learning models, and scale existing architecture.
Typical responsibilities range from evaluating the current data architecture to keeping databases secure. Depending on your organization and industry, your day-to-day tasks might include:
Translating business requirements into databases, data warehouses, and data streams
Creating procedures to ensure data accuracy and accessibility
Analyzing, planning, and defining 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 devise and implement data strategies, build models, and assess shareholder needs and goals
Researching data acquisition opportunities
Developing application programming interfaces (APIs) to retrieve data
Curious about data architecture? Get an overview of common database architectures through this video.
The volume of data that businesses and organizations deal with every day continues to grow rapidly. It's a critical element for business leaders who rely on data to make sound decisions. It's also important to consumers who want to make sure that their data is kept safe.
Data architects can use their skills in a variety of roles they may fill. Examples include the following:
Data architects define an organization's data vision and put it into practice.
Project managers oversee projects associated with the planning and building of data architecture.
Cloud architects employ company data in a cloud environment for optimal performance.
Security architects design and employ safeguards to ensure data confidentiality, integrity, and availability.
Machine learning architects design scalable systems for use with machine learning and artificial intelligence (AI) models.
The average annual base salary for data architects in the US is $137,749 according to Glassdoor (October 2024) [1]. Your salary will depend on factors like where you work, your level of experience, and the industry you work in, among others. For example, data architects working in major metropolitan areas like San Francisco and New York tend to earn salaries higher than the national average.
Data is an increasingly important component of businesses across many industries, which may account for the demand for data architects. The US Bureau of Labor Statistics (BLS) projects that careers working with databases and data will increase by 9 percent between 2023 and 2033 [2].
To become a data architect, you’ll need a mix of job-specific and more general workplace skills that empower you to leverage data tools and technologies to help data drive business goals. Some of the useful skills you might need:
Data mining to uncover patterns, anomalies, and correlations in large data sets
Data management to efficiently and cost-effectively collect, store, and use data
Coding languages like Python and Java to develop applications for data analysis
Machine learning to build scalable systems for handling big data
Structured query language (SQL) to manipulate data
Data modeling tools like ERWin or Visio to visualize metadata and database schema
Communication skills to help you effectively collaborate with other departments
Problem-solving and analytical skills to safeguard data integrity, security, and organization
Time management and the ability to multitask so that you can accomplish tasks and complete projects in a fast-paced environment
Developing the right skills is a big part of becoming a data architect. If you’re interested in this advanced data career, here’s a quick guide on how to get started.
A bachelor’s degree is the most common entry-level requirement for data architects, according to the BLS [1]. Consider a degree in computer science or data science to start building the skills you’ll need on the job.
Taking courses in operating systems, technology architecture, data management, database systems, and systems analysis can give you a solid foundation of knowledge and skills that can translate to professional expertise.
Many boot camps, workshops, and courses available online can sharpen your skills in specific areas of data management. If you’re new to the world of data, you might consider an introductory program, like the Google Data Analytics or IBM Data Analyst Professional Certificate. As you advance, consider classes in more advanced topics, like Python, SQL, or data warehousing.
A job as a data architect is rarely an entry-level position. Instead, employers typically look for data architects with at least three to five years of experience in a related field such as database administration, programming, managing data systems, or a similar role. You might start out as a data analyst, data engineer, or solution architect and work your way up.
Read more: How to Land a Data Science Internship
Once you’ve started gaining experience, you might also opt to pursue a professional credential to enhance your resume. These are some options you might consider:
Certified Data Professional (CDP): This credential from the Institute for Certification of Computing Professionals allows applicants to choose from specializations like data analytics and design, business analytics, data integration and interoperability, data warehousing, enterprise data architecture, and data management.
Certified Data Management Professional (CDMP): This widely-known data architecture certification is offered by the Data Management Association. It offers four certification levels depending on the amount of experience you have.
IBM Certified Data Architect - Big Data: Industry leaders at IBM offer this certification geared toward those who design the large-scale and complex data processing systems needed for big data architectures.
Data architects design, manage, improve, and troubleshoot information systems and computer architectures. Having skills in data architecture can open professional possibilities across a variety of industries. If you’re ready to take the first step toward a career in data, consider enrolling in the Google Data Analytics or IBM Data Engineering Professional Certificates. Build job-ready skills in less than six months as you learn at your own pace.
Glassdoor. “How much does a data architect make? https://www.glassdoor.com/Salaries/data-architect-salary-SRCH_KO0,14.htm.” Accessed October 3, 2024.
US Bureau of Labor Statistics. "Database Administrators and Architects, https://www.bls.gov/ooh/computer-and-information-technology/database-administrators.htm." Accessed October 3, 2024.
Editorial Team
Coursera’s editorial team is comprised of highly experienced professional editors, writers, and fact...
This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.