Principal Enterprise Architect

Overview

Department Overview

As a key member of the global enterprise architecture team that defines enterprise architecture strategy, north star capability and architecture blueprints, architecture standards, and drives holistic execution and realization of the architecture vision, the principal architect – enterprise data, analytics, and AI will be playing a critical role in providing the architecture thought leadership along with execution influence across our global technology and business organizations.

• Establish complete enterprise-level technology vision, strategy, standards, and capability roadmaps that set coherent context and direction connecting key enterprise data, analytics and AI initiatives for consumer, restaurant and company platforms.
• Design and develop enterprise data, analytics and AI target state architectures, standards, and specifications supporting current and future business needs.
• Represent EA point of view in critical initiatives to advise and develop short and long-term products and platforms roadmaps.
• Collaborate closely with data and solution architects to provide mentorship and gain alignment for design, implementation, and standardization.
• Implement EA capability modeling framework and design principles to establish the to-be state architecture, capability domain boundaries, and strategy for evolution.
• Define objectives and key results and critical metrics for EA data, analytics and AI foundations practice and drive measurable outcomes.
• Lead highly critical initiatives and drive key technology decisions and alignment at executive level.
• Mentor other architects and play a key role in maturing the enterprise architecture practice.
• Ability to partner with business and technology stakeholders to define and communicate values and outcomes of new or evolving capabilities.
• Strong interpersonal communication and collaboration skills; systems thinker capable of analyzing complex problems from technology, business model, process, and organizational perspectives.
• Ability to manage ad hoc demands along with organizational priorities and set realistic expectations.
• A self-initiated influencer with strong stakeholder management.

• Master’s degree in computer science, data science, AI or related field.
• Experience with data platforms and distributed data processing patterns & tools.
• Deep understanding in the major areas of Machine Learning, Predictive & Generative AI.
• Proven experience in architecting and deploying data, analytics, and AI solutions.
• Expertise in the areas of model architecture, data engineering, data governance and ML engineering.
• Experience in designing solutions for prediction, classification, clustering, anomaly detection, conversational agents, and information retrieval.
• Strong understanding of various AI architecture patterns & techniques.
• Experience with operationalizing machine learning systems using MLOPS.
• Strong expertise with cloud, on-premises, and hybrid deployment models.
• Proven expertise of building AI, ML, Data Solutions using major cloud provider technologies.
• Strong analytical and architectural modeling skills; well-versed in key architecture concepts and principles, including DDD, microservices, REST APIs, viewpoints, and perspectives.
• Experience with all facets of architecture and engineering including application development, platforms, infrastructure, security, and deployment; experience delivering large-scale cloud-native solutions.
• Exposure to an enterprise-level, global technology landscape and a proven ability to establish standards and define future roadmaps for a global company.
• Ability to partner with business and technology stakeholders to define and communicate values and outcome of new or evolving capabilities.
• Strong interpersonal communication and collaboration skills.
• Systems thinker.
• Ability to analyze complex problems from technology, business model and process, as well as organizational lens.
• Ability to manage ad hoc demands along with organizational priorities and set realistic expectations.
• A self-initiated influencer, and strong stakeholder management.

• Professional Level AI/ML/Data & Analytics Certifications
• Pr…