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About the Role

The Senior Director, Data Architecture simplifies and unifies RBC's data architecture across the full lifecycle, owning the target data architecture and standards that make data machine-readable for AI agents. Success means fewer data stores and point-to-point feeds, one trusted source for each critical data element, and data products agents can find and use within their entitlements.

Responsibilities

Run continuous inventory of data platforms and stores across RBC’s stacks.
Deploy automated architecture review and decision record workflows powered by agents to scale governance and documentation.
Establish audit trails of agent data access tied to entitlements.
Implement evals to validate whether agents can answer correctly from data products.
Define human-in-the-loop thresholds and ensure agents meet regulatory expectations for auditability and transparency.
Name the authoritative source for every critical data element.
Own the canonical data model and business glossary alignment.
Set the standard for producer data contracts covering schema, semantics, quality rules and SLAs.
Establish feedback loops where agent usage and failures feedback to producers.
Contribute to data distribution platform architecture and the standard ingestion patterns.
Move data once, reliably and traceably.
Operate a roadmap to retire point-to-point interfaces.
Enable agents to assist in architecture assessment, governance documentation, and exception tracking at scale.
Define what counts as a data product and the minimum metadata each must carry.
Build the semantic layer and ontology that lets agents interpret data, not just locate it.
Set the agent-access pattern for data products.
Include unstructured data with appropriate chunking, embeddings and freshness strategies.
Define the consumption archetypes with one supported pattern for each.
Feed curated, entitlement-aware data products into the common RAG substrate.
Design and implement evals for data products to validate whether agents can answer correctly from them.
Define human-in-the-loop thresholds and escalation patterns.
Align with model-risk governance frameworks to ensure agents operating on data products meet regulatory expectations.
Act as design authority through architecture review, decision records and exceptions.
Partner with the CDO, who owns policy and accountability, while this role owns how standards are built in.
Support regulatory lineage and jurisdiction-aware data placement for sovereignty.
Establish quality standards and practices specific to retrieval scenarios.
Ensure that data products used in RAG and agent workflows meet standards for accuracy and interpretability.
Inventory data platforms, stores and tools across RBC's stacks and give each a disposition.
Tie the roadmap to in-flight programs and to third-party rationalization.
Track and communicate measurable outcomes.
Establish strategy and standards for agent infrastructure.
Make principled decisions on build versus buy for agent-specific data infrastructure.

Requirements

15+ years in data architecture or data engineering, including 5+ years leading architects at enterprise scale.
Depth across lakehouse and warehouse platforms, streaming and CDC, data products and mesh, catalogs and metadata, semantic layers and knowledge graphs.
A track record of measurable simplification and modernization: data feeds rationalized, costs reduced, machine-readability coverage improved and agent task success rates on data products demonstrated.
Working knowledge of regulatory frameworks including BCBS 239, privacy regulation, OSFI E-23 (model risk) and OSFI expectations for data risk.
Clear view on making data AI-ready for retrieval, entitlement propagation, agent access and unstructured data workflows.
Experience designing and implementing data product governance, metadata standards and agent-accessible data architectures.
Able to align the CDO, platform engineering, business data owners and AI/ML leadership without direct authority over them.

Skills

Architectural Modeling
Critical Thinking
Data Architecture Development
Data Warehousing (DW)
Decision Making
Enterprise IT Architecture
Information Technology Consulting
Information Technology Trends
Multi-Level Communication
Physical Database Design

Location

RBC WATERPARK PLACE, 88 QUEENS QUAY W:TORONTO
Toronto
Canada

Work Type

Full time

Experience Level

Senior Director
15+ years in data architecture or data engineering
5+ years leading architects at enterprise scale

Benefits

A comprehensive Total Rewards Program including bonuses and flexible benefits
competitive compensation
commissions
stock where applicable

About the Company

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC.
We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world.
Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities.
RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.
Expand your limits and create a new future together at RBC.
Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.