Director, Enterprise Data Architecture - Data Strategy

We seek a strategic individual contributor to join our Enterprise Data architecture team as a Director, Enterprise Data Architecture. This leadership role is responsible for designing critical enterprise data strategy in consultation with Sun Life’s business and enterprise partners, including the holistic alignment of technologies, standards, and practices that enable Sun Life to deliver world class data and analytic systems. This role will directly report into the Global Head (AVP) of Data Architecture.

In this role you will strategically guide the evolution of our enterprise data architecture 'north star' to support advanced data architectures such as event streaming, and Data Fabric and Mesh on cloud. This is an innovation opportunity to gain experience with AI and ML initiatives on cloud for voice and text data.

What will you do?  

• You’ll engage and lead the data strategy engagements with business line executives, and define data architectures for enterprise engagements.
• Develop data architecture patterns, define playbooks and technologies 
• Establish and provide governance on enterprise data architecture and technology standards.
• Define and create Semantic Layer, Ontologies and Knowledge Graphs.
• Create and present tools/tech proposals and evaluations at Enterprise Architecture Governance councils
• Analyze structural and enterprise data architecture requirements to best enable new software and applications
• Apply and enforce enterprise data architecture best practices to all enterprise solution architecture and design areas, including cloud native AWS, hybrid cloud, and on-prem. This includes areas such as Operational Excellence, Security, Reliability, Performance Efficiency, and Cost Optimization.
• Collaborate with all regions to provide enterprise data architecture best practice and guidance on various delivery / implementations.
• You will also roll-up your sleeves and help the project teams with their complex technical issues from the enterprise data architecture point of view.
• Partner with the Data and Analytics teams to lead technology POCs and pilots in the data and analytics domain.
• Provide enterprise data architecture leadership and guidance on the design of end-to-end solutions for building data & analytics applications on cloud and on-premise platforms 
• Coordinate with data life cycle management program in all aspects of the delivery 
• Coordinate with the Data Science department to identify future needs and requirements 
• Mentor other data systems designers (Data Architects), both within your team and within other Digital Business and Technology Services, or other Business units, in order to support solution development and application of best practices. 
• Provide enterprise data architecture guidance to the solutions design team to drive data & analytics strategy across the enterprise  
• Provides architecture consultation for the evaluation of complex data and software systems. 
• Prior hands-on experience in designing and delivering data analytics solutions with proven business value.

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What do you need to succeed?  

• Strategic enterprise data architecture engagement skills with executive level stakeholders.
• 3+ years with cloud-based data architecture in a modern AWS environment. While AWS is preferred, for this particular role we can instead consider modern Azure or GCP cloud-based data architecture experience.
• Approximately 15+ years of build/design experience related to data service design, building data architecture, with prior experience leading end to end implementations.
• Strong knowledge on MDM (Master Data Management), RDM, Data Modeling techniques, Data architecture patterns
• Defining and creating Semantic Layer, Ontologies and Knowledge Graphs.
• Any additional experience with GraphQL, Random Forest and Tree, and ModelOps would be an asset, but not necessarily required.
• Background of working with data governance and its application 
• Experience in Machine Learning/AI methodologies and event streaming is an asset.
• Experience with technologies such as Kafka, Glue, Lambda, Redshift and/or Snowflake, and Informatica IICS, (or similar).
• Experience with data analytics and visualization using any modern age tools such as AWS Sagemaker, R Studio, Tableau (or similar).
• Extremely strong communication, critical thinking, conceptual and analytical skills.
• Excellent collaboration and leadership skills, a proven ability to adapt to challenges, and a strong interest in coaching and mentoring colleagues.