Data and Solution Architect

Job Purpose

The Data and Solution Architect is responsible for defining, governing, and advancing the enterprise data architecture required to enable scalable, trusted, and responsible AI solutions in the AI Hub.

Key Accountabilities

• Lead the design of logical, physical, and semantic data architectures to support AI, advanced analytics, GenAI and Agentic AI use cases
• Define AI-ready data models, feature-oriented structures, and analytics-ready data assets aligned to enterprise data platforms
• Ensure architectural alignment between data platforms, AI tooling, and MLOps pipelines
• Support design and governance of the Foundry Ontology layer as the enterprise semantic backbone for AI use cases
• Work closely with Data Architecture and Governance teams, define and enforce data standards, metadata practices, naming conventions, and master/reference data patterns for AI use cases
• Partner with Data Governance, Legal, and Compliance teams to ensure responsible and compliant AI data usage
• Enable and support AI use case enablement and POCs, experimentation environments, and sandbox platforms
• Own the data architecture stage-gate process across POC, expanded pilot, and production phases; define and maintain AI-readiness scorecards to assess data asset maturity at each stage
• Architect integrations across source systems, data platforms, analytics tools, and AI services
• Evaluate and onboard new data sources and technologies to meet evolving AI requirements
• Define reference architecture and architectural guardrails for cloud, hybrid, and global deployments
• Lead/support solution architecture development for projects/products, where necessary

Collaboration, Review & Enablement

• Serve as a data and solution architecture authority for AI-related initiatives and design reviews
• Mentor junior architects, data engineers and provide architectural guidance to delivery teams
• Contribute to AI Hub (COE), communities of practice, standards bodies, and architecture review forums

Qualifications, Experience, And Skills

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering/ Data Science, or related field
• 8+ years of experience in data architecture, solution architecture, enterprise data platforms, or analytics architecture
• Demonstrated experience supporting AI/ML, advanced analytics, or data-driven product initiatives
• Experience operating in federated governance or hub-and-spoke operating models
• Experience with data profiling and data quality management