Senior Manager, Data Quality & Governance USWM

Data Control Layer Operational Lead

What is the opportunity? US Wealth Management is evolving toward a domain-driven, data product-oriented architecture to enable scalable analytics, regulatory transparency, and AI-powered advisor insights. Achieving this requires moving beyond policy-driven governance to embedded, operational data control at scale. This role is responsible for turning governance into execution—ensuring data across critical domains (Client, Account, Positions, Transactions, etc.) is accurate, traceable, and fit-for-purpose. You will act as the operational lead of the Data Control Layer, embedding data quality, lineage, and governance directly into data products and pipelines, and ensuring domain teams are accountable for data outcomes.

What will you do?

Drive Enterprise Data Adoption

• Lead the rollout and adoption of data platforms, data products and AI-enabled insights across Wealth Management
• Define and execute data enablement strategies aligned to key business priorities (e.g., advisor productivity, client lifecycle, credit & lending insights)
• Ensure new capabilities are operationalized, not just delivered

Operationalize Data Products & Domains

• Partner with Business Strategy, Data Product, Data Engineering, and AI teams to translate outputs into business-consumable assets
• Develop enablement frameworks for domain-based data (e.g., Client, Account, Positions, Transactions) to ensure clarity in definitions and usage
• Establish playbooks for how data products are used in real workflows, not just how they are built

Lead Data Literacy & Training Programs

• Design and deliver targeted training programs for advisors, field leadership, and business partners
• Build tiered data literacy models (basic → advanced → AI-enabled decisioning)
• Enable users to confidently interpret metrics, KPIs, and AI-driven insights

Own Communication & Engagement Strategy

• Create clear, consistent communication on new data capabilities, changes, and value delivered
• Run internal campaigns to drive awareness and behavioral change
• Act as the "voice of the user" back into Data & AI teams

Bridge Business and Data Teams

• Engage Business Data Strategy team to translate business needs into enablement requirements, not technical specs
• Identify friction points in adoption and work with product/engineering teams to resolve
• Ensure alignment between what is built and what is actually used

Measure Adoption & Value Realization

• Define and track KPIs such as:
• Data product adoption rates
• Usage frequency and depth
• Advisor productivity lift tied to data usage
• Establish feedback loops to continuously improve enablement efforts

What do you need to succeed? (Must-have)

• Strong understanding of wealth management workflows (advisor experience, client lifecycle, lending/credit, reporting)
• Experience driving adoption of data platforms, analytics tools, or AI solutions
• Proven ability to translate complex data concepts into business-friendly narratives and workflows
• Experience designing and delivering training, enablement, or change management programs
• Familiarity with domain-driven data concepts and data products
• Strong stakeholder management across business, digital, and technology teams
• Analytical mindset with ability to define and track adoption and value metrics

Nice to have

• Experience with tools such as Snowflake, Power BI / Tableau
• Exposure to AI/GenAI use cases in financial services (e.g., advisor insights, client intelligence, automation)
• Knowledge of data governance, data quality, and metadata frameworks
• Background in change management methodologies (e.g., Prosci, Agile transformation)
• Experience enabling self-service analytics environments

What's in it for you?

• Opportunity to shape how data and AI are actually used at scale in a modern Wealth Management firm
• Direct impact on financial advisor productivity and client outcomes
• High visibility role operating across business, data, and AI leadership
• Ability to build a foundational capability (Data Enablement) that is often the difference between success and failure in data transformations
• Work at the forefront of integrating data domains, data products, and AI into real business workflows

The good-faith expected salary range for the above position is $90,000 - $160,000 depending on factors including but not limited to the candidate's experience, skills, registration status; market conditions; and business needs. This salary range does not include other elements of total compensation, including a discretionary bonus and benefits such as a 401(k) program with company-matching contributions; health, dental, vision, life and disability insurance; and paid time-off plan.

RBC's compensation philosophy and principles recognize the importance of a highly qualified global workforce and plays a critical role in attracting, engaging and retaining talent that:

• Drives RBC's high performance culture
• Enables collective achievement of our strategic goals
• Generates sustainable shareholder returns and above market shareholder value