Job Description Summary
As the Data Analyst, you will provide expertise for Data Management spanning both platforms and projects. At the core of the role is a detailed understanding of Data management principles and the ability to apply them to meet business and client data requirements. Your role is to ensure that data is well documented and managed across RBC Investor Services. You will be called on to find solutions to complicated data requirements and lead the design, development, testing and delivery.
As a member of a dynamic, fast paced team, this role brings strong data analysis skills and leadership, effective written and verbal communication skills, a strong work ethic and a demonstrated capability to multi-task effectively. This role requires strong interpersonal, organizational and problem-solving skills as well as a demonstrated sense of urgency to respond to changing priorities at times. This is complemented by a positive attitude and a willingness to take accountability for results achieved.
Job Description
What will you do?
- Collaborate with product, business development, Client Ops and digital teams on gathering data requirements.
- Analyze data within existing legacy data delivery channels, understand/translate business rules and define data requirements for delivering through modern tools and channels.
- Actively lead and engage in agile-like and business-led initiatives across a matrix environment.
- Leverage data to create efficiencies and reducing business/client risk.
- Build & enhance Data quality frameworks and operating models, which will deliver measurement, execution, monitoring, analysis and resolution support for datasets.
- Consult & confirm critical data elements (CDEs) with business, SME and Domain Experts for implementation of Data Quality Rules.
- Coordinate with data engineers to define Data flows and Data Quality measuring Points
- Provide weekly updates for actively running data quality rules for Master Reference Data and share reports with Stewards
- Actively manage the status of data quality rules enabled on datasets and investigate identified exceptions
- Build “Artificial Intelligence & Machine Learning” solutions that can identify data anomalies within active production pipelines
- Investiga