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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?

In this article, you'll learn more about data architects, including what they do, how much they earn, and how to become one. Afterward, if you want to learn in-demand data architecture skills, consider enrolling IBM Data Architecture Professional Certificate.

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IBM Data Architecture

Launch your career as a data architect. Learn in-demand skills like data engineering, database management, and data architecture in less than 5 months.

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Skills you'll build:

Databases, Data Analysis, Data Management, Network Security, Leadership and Management, Data Architecture, Data Engineering, SQL, Data Governance and Compliance, Database Management, Data Structures, Cloud Computing, Big Data, Data Analysis Software, ETL and Big Data Processsing, Data Science, Database (DBMS), Information Engineering, NoSQL, Risk Management, Data Security, Data Governance, Data Privacy, Encryption Techniques, Database Security, Database Servers, Relational Database, database administration, Star Schemas, Data Lakes, Snowflake Schemas, Cubes, Data Warehousing, Data Marts, Rollups, Relational Database Management System (RDBMS), Create, Read, Update And Delete, MySQL, Postgresql, Database (DB) Design, Database Architecture, Cassandra, Cloud Database, Cloudant, Mongodb, Extract Transform and Load (ETL), Shell Script, Linux, Linux Commands, Bash (Unix Shell), Apache Kafka, Data Pipelines, Data Engineer, Apache Airflow, System modernization, EDA, Digital governance, Data Migration, SparkSQL, Apache Hadoop, Apache Spark, SparkML, Data Storage, Data Architectures, Data Integration, System Modernization, Digital Governance, Enterprise Data Architect (EDA)

What is a data architect?

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. 

What does a data architect do?

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 in this lecture from the IBM Data Architecture Professional Certificate.

Types of data architects

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.

Is data architect the same as data engineer?

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. 

Read more: What Is a Data Engineer? A Guide to This In-Demand Career

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IBM Data Engineering

Prepare for a career as a Data Engineer. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from IBM. No prior experience required.

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Generative AI, Database Security, Database Servers, Database (DBMS), Relational Database, database administration, Star Schemas, Data Lakes, Snowflake Schemas, Cubes, Data Warehousing, Data Marts, Rollups, Cassandra, Cloud Database, Cloudant, Mongodb, NoSQL, Machine Learning Pipelines, Data Engineer, Apache Spark, SparkML, Machine Learning, SparkSQL, Apache Hadoop, Big Data, Data Generation, Querying Databases, Convolutional Neural Networks, Information Engineering, Apache Kafka, Extract Transform and Load (ETL), Data Pipelines, Apache Airflow, Pandas, Data Analysis, Data Science, Numpy, Python Programming, Google Looker Studio, IBM Cognos Analytics, Data Visualization, Dashboards, Business Intelligence, Relational Database Management System (RDBMS), Postgresql, Database (DB) Design, MySQL, Database Architecture, Shell Script, Linux, Linux Commands, Bash (Unix Shell), Leadership and Management, Databases, Data Management, Relational Databases, Data Visualization Software, SQL, Web Scraping, Network Security, Cloud Databases, Jupyter notebooks

Data architect skills 

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: 

Technical data architect skills

• 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

Workplace skills

• 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

Data architect salary and job outlook

The average annual base salary for data architects in the US is $142,986, according to Glassdoor (April 2025) [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]. Read more: What Is a Data Architect’s Salary?

How to become a data architect

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. 

1. Consider a degree in data or computer science. 

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. 

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2. Build a foundation in data. 

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. 

3. Start with an entry-level job in data.

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

4. Earn a data-centric certification. 

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. 

Read more: 5 Data Engineer Certifications: Which One Is Right For You?

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Preparing for Google Cloud Certification: Cloud Architect

Advance your career in cloud architecture.

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Critical Thinking, Google Cloud Platform, DevOps, Cloud Computing, Virtual Private Network (VPN), Load Balancing, Autoscaling, Virtual Machine, Network Architecture, Google Compute Engine, Google App Engine (GAE), Disaster Recovery, Site Reliability Engineering, Data Store, Cloud Storage, Debugging

Build your data architect skills on Coursera

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. Start building your skills with one of these programs on Coursera:

For foundational data skills, explore the Google Data Analytics Professional Certificate. Gain an immersive understanding of data practices, learn how to clean and organize data for analysis, and build skills using analytical tools like spreadsheets, SQL, and R programming.

To launch your career as a data architect, enroll in the IBM Data Architecture Professional Certificate. Build job-ready skills you need to succeed in the field, including database design, data engineering, and database management.

For cloud architecture, try the AWS Cloud Solutions Architect Professional Certificate. Gain the skills and knowledge to design architectural solutions on AWS and prepare for your AWS Certified Solutions Architect - Associate exam.

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IBM Data Architecture

Launch your career as a data architect. Learn in-demand skills like data engineering, database management, and data architecture in less than 5 months.

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Average time: 4 month(s)

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Skills you'll build:

Databases, Data Analysis, Data Management, Network Security, Leadership and Management, Data Architecture, Data Engineering, SQL, Data Governance and Compliance, Database Management, Data Structures, Cloud Computing, Big Data, Data Analysis Software, ETL and Big Data Processsing, Data Science, Database (DBMS), Information Engineering, NoSQL, Risk Management, Data Security, Data Governance, Data Privacy, Encryption Techniques, Database Security, Database Servers, Relational Database, database administration, Star Schemas, Data Lakes, Snowflake Schemas, Cubes, Data Warehousing, Data Marts, Rollups, Relational Database Management System (RDBMS), Create, Read, Update And Delete, MySQL, Postgresql, Database (DB) Design, Database Architecture, Cassandra, Cloud Database, Cloudant, Mongodb, Extract Transform and Load (ETL), Shell Script, Linux, Linux Commands, Bash (Unix Shell), Apache Kafka, Data Pipelines, Data Engineer, Apache Airflow, System modernization, EDA, Digital governance, Data Migration, SparkSQL, Apache Hadoop, Apache Spark, SparkML, Data Storage, Data Architectures, Data Integration, System Modernization, Digital Governance, Enterprise Data Architect (EDA)

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AWS Cloud Solutions Architect

Start here to become an AWS Solutions Architect. Gain the skills and knowledge to design architectural solutions on AWS and prepare for your AWS Certified Solutions Architect - Associate exam.

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Serverless Computing, Solution Architecture, Architecting on AWS, Cloud Computing Architecture, Amazon DynamoDB, Amazon Web Services, Data Architecture, Scalability, Identity and Access Management, Data Lakes, Amazon S3, Cloud Architecture, AWS Management Console, AWS Identity and Access Management (IAM), AWS Certification Preparation, Cloud Computing, Amazon Elastic Compute Cloud, Amazon CloudWatch, AWS Identity and Access Management, Networking on AWS, aws security, Software Architecture, Data Management, Data Analysis, AWS Account Management, Data Visualization, Data analytics, Data science, Data governance, Data lake architecture, Machine Learning, Data engineering, Amazon Web Services (Amazon AWS), Cloud Computing Security, AWS cloud