Data Architects design the frameworks and standards that determine how data is collected, stored, integrated, and accessed across an organization. They create data models, define database structures, establish governance policies, and ensure systems can scale securely while remaining compliant with regulations. Working closely with data engineers, analysts, and business leaders, they translate business requirements into robust technical architectures spanning cloud platforms, data warehouses, and data lakes.
| Entry level | $95,000 |
| Median | $140,000 |
| Senior | $175,000 |
| Top 10% | $210,000 |
| Job growth | +8% |
| Professionals in the USA | 0.2 million |
| Typical hours/week | 42 hrs |
| Remote work share | 55% |
| Annual job openings | 18,500/yr |
| Demand | High |
AI tools are increasingly assisting with schema generation, documentation, and data pipeline optimization, but strategic architecture decisions still require deep human judgment. Data architects are shifting toward overseeing AI-augmented tooling rather than being replaced by it. The role is evolving to include governance of AI/ML data infrastructure itself.
Automation exposure: Routine tasks like generating ER diagrams, writing boilerplate SQL/DDL scripts, basic data cataloging, and initial documentation drafts can be automated with AI tools.
The human edge: Data architects provide strategic vision, cross-functional stakeholder alignment, deep contextual understanding of business needs, risk assessment for compliance/security, and judgment calls on trade-offs between cost, scalability, and performance that AI cannot fully replicate.
Figures are estimates for exploration — verify current data with BLS.gov.