2026 Wealth Management, Fall Data Analyst (4-16 months)

RBC•Vancouver, BC

11d

About The Position

RBC Wealth Management is a part of Royal Bank of Canada (“RBC”), one of the largest providers of financial services in the world. RBC Wealth Management Canada is comprised of six complementary lines of business which are supported by over 250 wealth professionals through our RBC Family Office Services team. Together, we provide our clients an unmatched experience. Your application will be reviewed for consideration across multiple roles within the following areas: RBC Dominion Securities RBC PH&N Investment Counsel RBC Royal Trust RBC Private Banking RBC Wealth Management Financial Services RBC Global Asset Management What is the opportunity? We are seeking fall co-ops across several Data Analyst roles (including but not limited to the following: Data Analysts, Analytics Engineer, Data Team Co-Op, Data Engineer, Advisor Sales Analyst) to join the RBC Wealth Management Team. If you are passionate to learn about data engineering and data products delivery practices, please read on. What will you do? 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

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)

Nice To Haves

Exposure to Snowflake or cloud data platforms.
Basic understanding of AI/ML workflows (e.g., data preparation, model input/output).
Must be a self-starter, with strong analytical and problem-solving skills
Ability to work in teams and collaborate effectively with people in different functional areas
Excellent interpersonal and highly developed communication skills (verbal and written)

Responsibilities

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.

Benefits

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 service

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