AI & Data Analytics Architect

About the role

The AI & Data Analytics Architect role is responsible for designing and guiding the implementation of enterprise-wide AI, data analytics, and data architecture platforms and integrated solutions, primarily in the cloud. As a member of the Solutions Architecture team, this role bridges business strategy and technical execution by translating organizational goals into secure, governed, and scalable data and AI architecture.

Responsibilities

• Architect and guide the implementation of enterprise-wide artificial intelligence and data analytics tools and solutions using approved platforms, tools, and services.
• Develop end-to-end architecture solutions, including operational and analytical systems, ensuring alignment with enterprise policies and standards for data governance and security.
• Design end-to-end data pipelines, storage systems, and analytics architectures (batch or real time) using Azure services.
• Design solutions that integrate AI and ML models into data solutions, leveraging Azure Machine Learning, Microsoft Foundry, approved LLM services, and cognitive services for predictive and generative AI use cases.
• Provide solutions that incorporate data security, compliance, and governance frameworks to ensure data reliability, quality, and security.
• Help define enterprise governance and AgentOps patterns for AI and agent solutions, integrating security, Responsible AI guardrails, evaluation, observability, cost controls, and lifecycle management into repeatable, production-ready practices.
• Design data solutions using modern data platform capabilities (e.g. Lakehouse, warehouse, semantic models) leveraging primarily Azure services for unified data and AI governance while balancing existing legacy data warehouse architectures.
• Contribute to the development and adoption of enterprise AI and data architecture patterns, reusable solution templates, and technical standards in collaboration with the AI CoE.
• Design solutions that leverage cloud services for AI tasks, ensuring security, compliance, and cost efficiency.
• Collaborate with senior leaders, users, enterprise architects, solution architects, data analytics team members, software engineers, and other stakeholders to understand requirements; provide effective, timely solutions; and mentor others as needed.
• Work with users and vendors to conduct evaluations of various technologies in support of solution design.
• Evaluate new tooling and solutions to further the organization's AI and data strategy, identifying opportunities to leverage AI to achieve business goals, and developing a roadmap for implementing these solutions.
• Partner with the AI CoE, Enterprise Architecture, and delivery teams to ensure AI and analytics solutions align with established governance processes and enterprise technology strategy.
• Maintain awareness of emerging products, features, and industry trends related to AI, machine learning, and analytics platforms.
• Support technology lifecycle planning and maintain the CMDB as needed.

Qualifications

• Bachelor’s degree required.
• 10+ years of professional experience with demonstrated progressive responsibility in database modeling, development, deployment, analytics, and related technologies.
• 4+ years of professional experience with cloud-based data and analytics architectures and implementations preferably Azure.
• 1–2 years of professional experience implementing AI solutions.
• Ability to design, plan, and lead long-term, high-level technological initiatives.
• Exceptional communication skills to bridge the gap between technical teams and non-technical stakeholders.
• Strong proficiency in AI/ML principles, MLOps, data engineering, and cloud platforms, particularly Azure and Oracle.
• Demonstrated deep understanding of the Azure data stack, data handling, ETL processes, and analytics.
• Demonstrated expertise in Azure data and analytics services.
• Demonstrated experience with data security and privacy protection measures.
• Proactively stay informed on new technologies and practices related to AI and data analytics.
• Ability to quickly and effectively evaluate and experiment with new technologies, translate that knowledge into information for others to learn quickly, and make recommendations based on the information at hand.
• Ability to quickly design solutions that meet requirements and provide business value.
• Results-oriented individual with strong problem-solving, influencing, consensus-building, and negotiating skills.
• Knowledge of on-premises, cloud, and hybrid data practices to deliver innovative solutions.
• Knowledge of the following tools:
• M365 Copilot, Copilot Studio, Microsoft Foundry, GitHub Copilot
• Azure Machine Learning, Microsoft Fabric, Power BI, Oracle Fusion Analytics, Microsoft Purview
• Azure Synapse Analytics, Azure Data Lake Storage (ADLS) Gen2, Azure SQL Database, Azure SQL Managed Instance, SQL Server, and SSIS
• Preferred knowledge of the following tools:
• Incorta, Azure Cosmos DB, Azure AI Search, WhereScape
• Demonstrated ability to work independently, follow direction, and take initiative.
• Demonstrated strong communication and interpersonal skills.
• Demonstrated ability to collaborate with cross-functional teams and solve complex problems.