Manager, Data Analytics

Royal Bank of Canada•Mississauga, ON

12h•Onsite

About The Position

RBC Insurance Investments is seeking a skilled Manager, Data Analytics, to help and scale our investment data and analytics capability. This role is suited for a well-rounded leader who can operate across the full analytics lifecycle – from raw data sourcing, transformation, and data modelling through to advanced visualization, business insights, and predictive analysis. The successful candidate will combine strong technical expertise with financial and business acumen. In addition to delivering robust datasets, dashboards, and analytical solutions, this individual will lead high-value analytical work that supports investment and balance sheet decision-making, including cash flow projections, and balance movement analysis.

Requirements

Bachelor’s degree in quantitative fields such as Finance, Mathematics, Statistics, Actuarial Science, Engineering, Computer Science, Economics, or related discipline.
3+ years of relevant experience in analytics, business intelligence, quantitative analysis, data engineering, financial modeling, or a related field.
Demonstrated experience delivering end-to-end analytics solutions and working directly with senior business stakeholders.
Experience leading projects, workstreams, or teams in a cross-functional environment.
Advanced Power BI capabilities, including data modeling, DAX, report design, and Power Query.
Strong SQL skills, ideally in Snowflake or similar cloud-based database platforms.
Hands-on experience with Python for data analysis, automation, forecasting, or modeling.
Strong understanding of structured financial data, time-series analysis, and large-scale datasets.

Nice To Haves

Master’s degree in a quantitative, financial, or analytical field is strongly preferred.
Experience in investment, insurance, asset management, treasury, banking, or other financial services environments is strongly preferred.
Experience in investment analytics, insurance investment, ALM, portfolio analytics, treasury analytics, or capital markets.
Familiarity with Bloomberg, Reuters, or other market and financial data platforms.
Exposure to cloud platforms and modern data ecosystems.
Experience with machine learning or advanced analytics techniques is an asset.
CFA, actuarial, data science, or analytics-related certifications are an asset.

Responsibilities

Lead the design and delivery of end-to-end analytics solutions, from raw data acquisition and transformation through to dashboarding, business insight generation, and user adoption.
Translate complex business questions into scalable data, reporting, and analytical solutions.
Ensure analytics outputs are accurate, well-governed, and aligned with business priorities.
Work with raw and curated data from multiple internal and external sources to create scalable, high-quality datasets for reporting and analysis.
Write and optimize SQL queries in Snowflake and other cloud-based environments.
Partner with data engineering and data squad teams to improve data pipelines, controls, and analytical data models.
Identify opportunities to enhance data quality, reusability, and operational efficiency across the analytics stack.
Lead the design and implementation of high-impact Power BI dashboards for portfolio managers, actuaries, finance, risk, and senior leadership.
Develop robust semantic models, DAX logic, and Power Query transformations to support flexible and trusted reporting.
Present complex analysis in a clear, concise, and business-relevant manner for a range of audiences, including senior management.
Lead analysis of investment and financial data, including positions, transactions, cash flows, balances, performance, and time-series data.
Develop forecasting and modeling solutions to support business needs, including balance sheet analysis, inflow/outflow projection, and related decision-support analytics.
Connect model outputs to business interpretation and strategic decision-making.
Partner with senior stakeholders across investment, actuarial, finance, risk, and product teams to identify opportunities where analytics can drive better decision-making.
Influence adoption by ensuring solutions are intuitive, relevant, and aligned to stakeholder needs.
Lead cross-functional delivery across business and technical teams, balancing strategic goals with execution realities.
Help build a strong analytics culture grounded in curiosity, ownership, and practical problem-solving.