Data Quality Analyst
3 weeks ago
What is the Opportunity?
As a member of Data Services, you will play a role in supporting RBC Capital Markets’ first line data solutions and delivery. This is a unique opportunity to assist the execution of key components of our first line data strategy including: centralized exception handling, data quality issue management, and data quality control implementation.
This role will face off directly with members of various regulatory operations teams, stakeholders from Capital Markets desks, and stakeholders within Business and Client Services (BCS).
You will be called on to find solutions to complicated data issues. Specifically you will have to monitor data quality controls, investigate data quality issues, identify data and process gaps, and facilitate the resolution of issues with various stakeholder teams.
As a member of a dynamic, fast paced team, this role brings strong data analysis skills, 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.
What Will You Do?
Understand data flows and transformations that are relevant to data usage. Perform analysis to find the cause of issues and facilitate the remediation of these issues.
Responsible for large scale multi-way comparisons of data against various internal and external sources to identify trends and to measure overall data quality.
Profile data and develop new data quality rules and controls, and work with implementation teams to ensure that controls align to business needs. Support the refinement of controls as requirements evolve.
Prioritize issues and data quality exceptions through measuring their material impact on business and regulatory processes. Escalate critical issues as needed.
Collaborate with stakeholders to understand the data issues and lead issue management initiatives.
Develop and implement reporting and data visualization dashboards to articulate trends and data quality measurements.
Support the root cause analysis of data issues utilizing advanced pattern recognition and machine learning.
Identify and coordinate system and process enhancements and improvements.
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