Wealth Management, Fall Data Analyst

RBC

Data Analyst role assisting in the development and delivery of data product solutions at RBC Wealth Management. Collaborating across multiple teams to improve data quality and efficiency.

Posted 5/1/2026internshipToronto • 🇨🇦 CanadaMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformKubernetesLinuxPythonSDLCSQLTableauUnix

About the role

Key responsibilities & impact

Assist in the development and delivery of data product solutions including building, customizing, and management of data pipelines, data integration tools, databases, data warehouses, and analytical systems
Lead “data hygiene” effort in on our CRM system to ensure accurate quality data
Develop and maintain data pipelines for extracting, transforming, and loading data across SQL Server, SAS, and Snowflake
Write efficient SQL queries and Python scripts to automate workflows and ensure data quality
Use in-house applications to process trades and monitor settlement workflows
Leverage tools such as Eagle, Charles River, Bloomberg, and Excel for data analysis and reporting
Support testing requirements for data products and services including testing automation
Support the development and execution of strategic initiatives in collaboration with internal and external stakeholders using our software development life cycle (SDLC)
Design, develop, implement, and support our emerging big data analytics capabilities through the development and maintenance of advanced data ingestion, processing, modeling and reporting capabilities
Process security, product and employee set up on Eagle system
Collaborate with engineers, analysts, and AI practitioners to prepare high-quality data for advanced analytics and business use cases
Review data quality monitors daily and address data quality issues with data stakeholders
Analyze data and data workflows to improve data quality
Work with cloud platforms (AWS, Azure, GCP) to deploy and manage data infrastructure

Requirements

What you’ll need

Have a strong quantitative background, a degree in math/statistics/computer science/engineering would be a plus
Experience working with SQL and large data sets and knowledge of AWS, cloud computing, or similar storage solutions
Manipulate, organize and retrieve data using formulas and logic functions (particularly vlookups)
Familiar with Kubernetes, Docker and containerization technologies and strong Unix/Linux/Bash scripting skills
Experience working with DevOps CI/CD pipelines and automated testing
Experience working within professional software engineering practices for the full software development life cycle, including coding standards, code reviews, source code management, build processes and testing
Desire to learn data capabilities such as data management, data governance, data mastering, data quality, data literacy, etc
Curiosity and willingness to learn about AI/ML and how data engineering supports it
Desire to learn data business intelligence tools (e.g. Excel, Tableau)

Benefits

Comp & perks

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 service

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

SQLPythondata pipelinesdata integrationdata warehousingdata analysisdata modelingUnix/LinuxBash scriptingDevOps CI/CD

Soft Skills

collaborationcuriositywillingness to learnproblem-solvingattention to detailcommunicationleadershiporganizational skillsanalytical thinkingstakeholder management