Director, Data Products & Semantics

RBC • Mississauga, ON

1d • CA$90,000 - CA$140,000 • Onsite

About The Position

We are building a governed consumption layer on our Snowflake data platform, a curated set of business-aligned data products and semantic definitions that make enterprise data trustworthy, discoverable, and usable at scale. We are looking for a director to own this capability end to end. This role sits at the boundary between data engineering and business consumption. You will define what "ready to use" means for our data, lead the team that builds it, and work closely with our Data Platform & Engineering team who owns the underlying data models, platform services, and production deployment. Together, you will ensure that what gets built is both technically sound and business relevant. You bring hands-on experience with the modern data stack, have built or led semantic/consumption layers before, and have evolved into a leader who can translate business needs into governed data products. You understand that the future of analytics is self-serve and increasingly AI-assisted, and that a well-defined semantic layer is what makes that future reliable.

Requirements

• Technical depth: Hands-on SQL experience and fluency with modern transformation tools (dbt or equivalent) on cloud data warehouses (Snowflake required). You can review code, contribute to designs, and hold engineering standards.
• Consumption layer experience: You have built or led a semantic layer, data products function, or governed mart/reporting layer before. You know the difference between a data model and a data product, and you've navigated that boundary in practice.
• Collaboration with platform teams: Experience working alongside (not above) data engineering or platform teams, shared standards, code review across team boundaries, joint delivery accountability. You respect the infrastructure that makes your layer possible.
• Leadership: Proven experience managing analytics engineers or similar technical roles. Track record of building small teams that deliver disproportionate impact through standards and leverage, not headcount.
• Business fluency: Ability to prioritize based on business value, communicate trade-offs to non-technical stakeholders, and drive adoption of governed data products over ad-hoc alternatives.
• Governance in complex environments: Experience establishing data governance, quality, and access standards in large or regulated organizations.
• Pragmatism: Ability to define long-term direction while delivering incrementally. Comfortable with ambiguity and competing priorities.

Nice To Haves

• Financial services or insurance domain knowledge.
• Experience with knowledge graphs or formal ontology frameworks.
• Familiarity with AI/ML feature stores or LLM context layers.
• Experience defining RBAC or row/column-level security policies on Snowflake.

Responsibilities

• Own the consumption layer: Design, deliver, and govern business-ready views and data products on Snowflake, defining entities, metrics, and datasets that serve BI, operational systems, and AI applications with consistent, trusted definitions.
• Build and lead a team: Hire, develop, and manage analytics engineers focused on consumption-layer design and delivery.
• Partner with Data Platform & Engineering: Work daily with the team that owns data modeling and platform infrastructure. They own the contracted data models and production deployment; you own what gets built on top and how it's presented to consumers. This is a tight collaboration, not a handoff.
• Partner with Analytics & Insights: Work with BI analysts and data consumers to identify needs, prioritize data product development, and ensure the layer evolves based on real usage.
• Define standards: Establish governance criteria for the consumption layer, naming conventions, metric definitions, testing, documentation, lineage, access policies, and maintain them as the platform scales.
• Coordinate across teams: Work with IT partners on security, compliance, and infrastructure; engage business domain owners as stakeholders; align with AI programs on data requirements.
• Enable self-serve and AI-readiness: Position the semantic layer as the foundation for self-serve analytics and generative AI use cases (text-to-SQL, contextual retrieval), where correctness depends on embedded business context rather than user expertise.

Benefits

• A Total Rewards program that includes flexible benefits, work/life balance and career development programs and investment and retirement savings plans
• Competitive pay and high-earning potential
• All the tools, training, and team support you need to grow your business and career
• Flexible work/life balance options
• RBCI software tools to boost your productivity and grow your business

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: No Education Listed