Data Architect

Role Summary

We are seeking an experienced Data Architect to lead enterprise data governance, data modelling, information architecture, and modern data platform initiatives.

The role will focus on building trusted, secure, and scalable data services that support AI, analytics, cybersecurity, risk management, and vulnerability management programs.

The customer wants someone who can set up and lead enterprise data governance, design data models, and build modern, secure data platforms on Azure that support AI, analytics, cybersecurity, and risk teams.

Key Responsibilities

• Define and implement enterprise data governance frameworks, standards, and operating models.
• Design conceptual, logical, and physical data models across relational, NoSQL, and graph databases.
• Develop taxonomy, metadata, data quality, lineage, classification, and information architecture standards.
• Architect secure data access models using RBAC, ABAC, and least-privilege principles.
• Lead integration of data platforms, APIs, data contracts, ingestion pipelines, and schema management.
• Establish data quality controls, governance processes, and ownership/stewardship models.
• Collaborate with Security, Risk, Privacy, Analytics, AI, and Engineering teams to deliver scalable data solutions.
• Create implementation roadmaps and provide knowledge transfer to internal teams.

Required Qualifications:

• Bachelor s degree in computer science, Information Management, Data Management, or a related field
• 10+ years of total experience in Data Architecture, Data Management, Governance, or Analytics
• 5+ years specifically leading enterprise data governance, metadata, data quality, or operating model initiatives
• Strong hands-on experience in data modeling, schema design, APIs, data integration, and governance frameworks
• Expertise in relational, NoSQL, and graph databases
• Experience working with Security, Risk, Compliance, Privacy, and Technology teams

Preferred Skills:

• Microsoft Azure Data Services and Microsoft Purview.
• Data Catalog, Metadata Management, and Data Quality tools.
• Experience supporting AI, Analytics, Cybersecurity, Risk, or Vulnerability Management programs.
• Background in large-scale, regulated enterprise environments.