A **data architect** is an [[Information technology|IT]] professional responsible for designing, creating, and managing an organization's [[Data architecture|data architecture]] — the structures, policies, and standards that govern how data is collected, stored, integrated, and used. The role sits at the intersection of [[Enterprise architecture|enterprise architecture]], [[Data management|data management]], and [[Business strategy|business strategy]], translating organizational requirements into coherent technical blueprints that ensure data is accessible, reliable, and secure. Data architects define the frameworks and models through which data flows across an organization, including [[Data model|data models]], [[Database|database]] designs, [[Data integration|integration]] patterns, and [[Metadata management|metadata]] standards. They work closely with [[Data engineer|data engineers]], [[Database administrator|database administrators]], and business stakeholders to align technical infrastructure with strategic goals. Core responsibilities typically include developing [[Conceptual schema|conceptual]], [[Logical data model|logical]], and [[Physical data model|physical]] data models; establishing [[Data governance|data governance]] policies; and evaluating technologies such as [[Data warehouse|data warehouses]], [[Data lake|data lakes]], and [[Cloud computing|cloud]] platforms. The role has grown in prominence alongside the rise of [[Big data|big data]], [[Artificial intelligence|AI]], and [[Data-driven decision-making|data-driven decision-making]], as organizations increasingly depend on well-structured data pipelines to support [[Business intelligence|business intelligence]] and [[Machine learning|machine learning]] initiatives. Data architects are distinguished from [[Data scientist|data scientists]] and [[Data analyst|data analysts]] by their focus on infrastructure and standards rather than analysis, and from [[Solution architect|solution architects]] by their specialization in data systems specifically.