Lead Data Modeler/Analyst

RBC • Toronto, ON

2d • Onsite

About The Position

The Trading & Execution Services (TES) Data Services team within Capital Markets Technology has elevated data to first-class citizen status, providing strategic solutions for the capture, retention, analysis, and reporting of all transactional data spanning the Capital Markets cross-asset front-office trading lifecycle. Our team is responsible for ingesting and managing cross-asset trading data on our cloud data lake. We consolidate pre trade data from internal RBC trading execution systems and external Independent Software Vendors (ISVs) to deliver high-quality, standardized data products that power front office decision-making across all asset classes.
We are building a world-class data organization that leverages artificial intelligence and modern cloud-native architectures to transform how capital markets professionals access and consume data.
We are looking for a Lead Data Modeler/Analyst to lead the design and delivery of enterprise-grade data models across our cloud data lake. This is a senior leadership position that requires equal command of technical depth and business acumen. You will own the end-to-end data modeling strategy, build and manage a team of data analyst professionals, and serve as the connective tissue between front office stakeholders and backend engineering teams.
This role demands a self-driven leader who can operate independently, engage confidently with senior stakeholders, and deliver results at pace in a complex, multi-asset trading environment.

Requirements

• Bachelor’s degree in computer science, Software Engineering, Information Systems, Mathematics, or related field
• 10+ years of progressive experience in data architecture, data modeling, and data strategy roles
• 6+ years working in capital markets with hands-on exposure to multiple asset classes (equities, fixed income, derivatives, FX, commodities) & deep understanding of capital markets trading workflows, trade lifecycle, and market data structures
• Demonstrated people management experience with a track record of building and developing high-performing teams
• Proven ability to operate at a senior level, influencing decisions and managing relationships with executive stakeholders
• Expert proficiency in data modeling methodologies (conceptual, logical, physical) and experience designing data architectures for cloud-native data lakes and lakehouses at enterprise scale
• Hands-on experience with industry-standard communication protocols like FIX (Financial Information Exchange).
• Advanced SQL and Python skills for data analysis, profiling, and transformation
• Solid understanding of ETL/ELT patterns, data pipeline orchestration, and real-time data ingestion
• Working experience with using AI tools to speed up data analysis & us AI for productivity improvement in space of data analysis, modelling & mapping generation.

Nice To Haves

• Familiarity with data from major financial ISVs and market data providers
• Demonstrated experience using AI/ML techniques for data analysis, data quality assessment, or automated model generation. Prior hands-on use of generative AI tools (e.g., Copilot or similar) applied to data engineering or modeling workflows
• Knowledge of regulatory data requirements (MiFID II, CFTC, Dodd-Frank) and their impact on data architecture
• Experience with data visualization and BI tools (Power BI, Tableau) for building executive-facing data products

Responsibilities

• Analyze cross-asset data from internal RBC systems and external ISV sources to understand data lineage, relationships, and gaps
• Design and implement standardized, scalable data models that serve as the foundation for a unified presentation layer organized by asset class and product
• Engage early in project lifecycles to conduct thorough data gap analysis and identify quality issues before they propagate downstream
• Partner with upstream source teams to define data contracts, track remediation efforts, and ensure sustained data quality improvements
• Liaise with adjacent teams to diagnose, adjust, and resolve data system issues across the trading data ecosystem
• Leverage generative AI tools and techniques as the primary methodology for data exploration, profiling, pattern detection, and model prototyping
• Coach and mentor direct reports to adopt AI-first workflows in their daily analysis and modeling activities
• Drive rapid proof-of-concepts using cloud data lake resources to demonstrate value and validate approaches for front office requirements
• Contribute to the broader data strategy for the QTS division and influence architectural decisions across the platform
• Liaise with external stakeholders & ISV to establish data connectivity with RBC for exchange of data & get sample data for analysis & work with them to remediate data gaps with respect to RBC requirements.

Benefits

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable
• Leaders who support your development through coaching and managing opportunities
• Ability to make a difference and lasting impact
• Work in a dynamic, collaborative, progressive, and high-performing team
• A world-class training program in financial services
• Flexible work/life balance options
• Opportunities to do challenging work

What This Job Offers

• Job Type: Full-time
• Career Level: Senior