This role works closely with Enterprise Architecture, Solution Architecture, Enterprise Data, Data Engineering, Data Science, Analytics, Infrastructure, Security, and Business teams to understand strategic priorities and define enterprise architecture solutions that support business outcomes. The role interacts closely with Data organizations across the enterprise and supports the delivery of client-centric business solutions through modern data management, analytics, and AI capabilities. Own, lead, and manage the overall Enterprise Data Architecture Strategy and Roadmap supporting Information Management, Data Management, Business Intelligence and Reporting, and Advanced Analytics. Develop and maintain a multi-year Enterprise Data Architecture strategy aligned with business priorities, technology modernization objectives, cloud adoption initiatives, and enterprise data transformation goals. Align with Sun Life's AI-ready Data Framework, and ensure that capabilities such as data quality, metadata, lineage, semantic models, governance, and data product standards mature effectively as required to support analytics and AI initiatives. Curate and prioritize enterprise data architecture investments to ensure alignment with business strategy and enterprise architecture objectives. Based on the tightly integrated nature of Data and AI, maintain joint accountability for developing and communicating integrated Data and AI roadmaps alongside AI Architecture and Engineering leaders. Support Data and Analytics organizations in translating strategic business requirements into scalable enterprise data architectures and enterprise information models. Define architecture standards and reference patterns supporting structured and unstructured data assets, including operational data, analytical data, documents, content repositories, and enterprise knowledge assets. Lead, coach, mentor, and develop a high-performing team of Directors, Architects, and Senior Consultants across geographies. Monitor regulatory, privacy,



compliance, retention, audit, and governance requirements and assess their impact on enterprise information management practices. Requirements

Minimum 10 years of experience in Enterprise Data Architecture, Information Architecture, Data Management, or related disciplines. Deep expertise in enterprise data architecture, information management, analytics platforms, and cloud-native data ecosystems. Demonstrated experience defining and implementing enterprise-scale data strategies that support business transformation initiatives. Deep understanding of client needs, market trends, and emerging technologies. Ability to manage through influence in a highly complex global environment. Ability to establish and maintain a high degree of trust and credibility with senior business and technology leaders. Strong consulting, communication, organizational, negotiation, and stakeholder management skills. Ability to communicate effectively with both technical and non-technical audiences. Demonstrated ability to bridge business strategy, enterprise data architecture, analytics, and AI enablement through scalable enterprise data foundations. Robust experience with modern data architecture, including Data Warehousing, Data Lakes and Lakehouse Architectures, Data Products, Metadata Management, Master and Reference Data Management, Data Lineage, Data Governance, Event Streaming Platforms (Kafka), Relational and NoSQL Databases, Graph and Semantic Technologies, Real-Time Data Platforms. Experience supporting Artificial Intelligence and Machine Learning initiatives through scalable data architecture, governance,



metadata, and information management capabilities. Strong understanding of AI data requirements, model lifecycle considerations, AI governance principles, and responsible AI practices. Minimum 2 years of hands-on experience designing enterprise-scale cloud-native data solutions on AWS. Strong knowledge of AWS services including: S3, Redshift, Glue, Athena, SageMaker, Lake Formation, CloudFormation. Experience with Azure cloud services is considered an asset. Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Information Technology, or a related discipline. Experience leading and managing a team of Solution Architects and working in a matrixed organization. Core Competencies

Demonstrates extensive expertise in Enterprise Data Architecture and Information Management, with a strong focus on developing scalable data strategies that align with business transformation initiatives. Proficient in leading teams and managing complex data ecosystems, ensuring compliance and governance while supporting AI and analytics capabilities. Highest-signal resume keywords

Enterprise Data Architecture Data Management Cloud-Native Data Solutions AWS Services Data Governance ATS Optimization Keywords

Hard Skills Data Warehousing Data Lakes Data Governance Metadata Management Master Data Management Data Lineage Event Streaming Platforms Relational Databases NoSQL Databases Graph Technologies Soft Skills Consulting Communication Organizational Skills Negotiation Stakeholder Management Certifications & Qualifications

Bachelor's Degree in Computer Science Master's Degree in Information Systems Industry Keywords

Enterprise Architecture Business Intelligence Advanced Analytics AI Governance Data Transformation Tools & Technologies

AWS S3 AWS Redshift AWS Glue AWS Athena AWS SageMaker AWS Lake Formation AWS CloudFormation Azure Cloud Services

#J-18808-Ljbffr

📌 AVP, Enterprise Data Architecture (Winnipeg)
🏢 Jobtailor
📍 Winnipeg