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Senior Director of Data Architecture

3 months ago

Old Toronto, Ontario, Canada Sun Life Full time
Position Overview

Role: Director, Enterprise Data Architecture

We are seeking a highly skilled and experienced professional to take on the role of Director of Enterprise Data Architecture. This position requires a deep understanding of external Client Data engagement analytics and operational data domains, essential for shaping our strategic data architecture. You will be instrumental in harmonizing the national customer data experience across various business units, with a focus on creating a comprehensive customer 360 view.

Your expertise in modern AWS data architecture environments will be crucial. This role is designed for a strategic individual contributor who will work closely with our Client Experience Office (CXO) to unify the client journey across the organization. You will lead the architectural design of critical data systems, collaborating with Sun Life's business and enterprise partners to ensure alignment of technologies, standards, and practices that facilitate world-class customer data and analytics systems.

The Data Architecture team is at the forefront of implementing innovative solutions that drive business opportunities at Sun Life. Reporting directly to the Chief Data Architect – Global, you will also collaborate with the Chief Data & Analytics Officer – Canada and the Chief Architect – Canada. Your responsibilities will include designing and implementing advanced data architectures, such as event streaming and data fabric on cloud platforms, to support sophisticated marketing initiatives. This role offers a unique opportunity to engage with AI and ML projects within the customer data landscape.

Key Responsibilities
  1. Oversee the conceptual framework of the client-oriented data domain, ensuring robust data architecture governance.
  2. Lead the integration of data and analytical products across the CXO ecosystem, from data collection to decision-making engines.
  3. Advocate for data design across business units to meet operational and analytical requirements aligned with the Chief Data Analytics Office.
  4. Engage with client executives to define data architectures for national-level customer data strategies.
  5. Provide mentorship and support to project teams facing complex technical challenges.
  6. Develop data architecture patterns and create comprehensive playbooks for data technologies.
  7. Assess structural requirements for new software and applications within the customer data domain.
  8. Conduct technology proofs of concept and pilot projects in collaboration with data and analytics teams.
  9. Present proposals and evaluations for customer data tools and technologies at Enterprise Architecture Governance councils.
  10. Guide the design and implementation of data and analytics applications on both cloud (AWS) and on-premise platforms.
  11. Coordinate with the Data Lifecycle Management program to oversee all delivery aspects.
  12. Collaborate with the Data Science department to identify future needs in the customer data domain.
  13. Apply best practices in solution architecture, covering operational excellence, security, reliability, performance efficiency, and cost optimization.
  14. Mentor data systems designers within your team and across other enterprise services to foster best practices.
  15. Establish governance on data architecture and technology standards, partnering with Data and Analytics delivery teams and Solution Architects.
Qualifications
  1. Over 10 years of experience in technology design and implementation related to data services and architecture.
  2. At least 2 years of experience with AWS cloud-based data architecture, including technologies like Glue, EMR, Redshift, and Lambda.
  3. Familiarity with open-source technologies such as Kafka, Python, and Spark.
  4. Minimum of 3 years leading technology design architecture and analytics for external customer data, with a preference for knowledge in Master Data Management (MDM).
  5. Experience with RDM and Data Modeling techniques, as well as evaluating data architecture patterns.
  6. Background in data governance and its practical applications.
  7. Familiarity with Machine Learning/AI methodologies and technologies such as Sagemaker, R, or Python is advantageous.
  8. Experience in architecting data analytics and visualization solutions using modern cloud-based and open-source tools.
  9. Preferred experience in the financial services sector, particularly in insurance.
Benefits
  1. Recognized as a Great Place to Work Certified organization for multiple categories.
  2. Flexible hybrid work model, allowing for work-from-home options.