Senior Manager, ALM Risk Transformation

RBC•Toronto, ON

4d•Onsite

About The Position

The Senior Manager will shape the next phase of our Asset-Liability Management (ALM) risk data strategy and supporting the transformation of our risk practices. This role will design, build, and optimize scalable data pipelines, data models, and analytics infrastructure to support RBC’s ALM risk and Non-Trading Portfolio Market Risk. This position bridges technical execution with strong business understanding, delivering reliable data solutions that enable timely risk insights, independent oversight, and effective implementation of RBC’s balance sheet risk framework.

Requirements

University degree or equivalent in a quantitative, technical, or financial discipline
Strong proficiency in Python for data pipelines, automation, and scripting
Solid experience with SQL and relational databases (MySQL, PostgreSQL, SQL Server, or equivalent), including designing and implementing ETL/ELT workflows and data transformation logic
Working knowledge of financial markets and products, including fixed income, linear interest rate (IR) derivatives; familiarity with market risk concepts such as sensitivity measures and stress testing
Excellent interpersonal skills and ability to communicate complex technical concepts clearly to non-technical stakeholders, both verbally and in writing

Nice To Haves

Expertise with Snowflake (or equivalent cloud data warehouse) and SQL optimization
Experience with big data processes (Spark, Airflow) including batch processing and/or real-time streaming technologies is preferred.
Deep understanding of the bank’s balance sheet composition and business lines

Responsibilities

Design, build, and optimize ETL/ELT pipelines that ingest, transform, and consolidate ALM risk data from multiple sources into a centralized data platform, streamlining aggregation of ALM risk exposures and reporting capabilities.
Develop optimized SQL transformations and data architectures to support reliable market risk measures, stress testing, and regulatory reporting.
Develop Python scripts and automation workflows to streamline data ingestion, validation, and quality controls.
Build and maintain self-serve dashboards (Tableau/Power BI), enabling risk teams to access timely and actionable risk insights.
Collaborate with risk managers, business partners, and IT to translate business requirements into scalable technical solutions; serve as both an independent risk fiduciary and a value-added partner to the business.
Ensure robust data governance and lineage documentation-encompassing transformation logic, data quality frameworks, and technical architecture standards.
Apply deep understanding of market risk concepts (sensitivity measures, stress testing, ALM frameworks) and financial products (IR derivatives, FX, repo) to inform data model design and risk infrastructure decisions.
Lead data engineering projects end-to-end, from requirements definition and IT delivery oversight to operational documentation and process guides, navigating ambiguity and driving sound decisions.