Business Insights Specialist

The Business Insights Specialist, Data Quality & Validation is an individual contributor responsible for the design, execution, validation, and ongoing monitoring of data quality controls supporting business rules, analytical models, and regulatory/management reporting. This role serves as a subject matter expert (SME) in data, focusing on data quality and partnering closely with business, analytics, technology, and governance stakeholders to ensure data is accurate, complete, consistent, timely, and fit for purpose across the end-to-end data lifecycle.

The role operates without direct people management responsibilities but carries enterprise-level accountability, influence, and decision authority over data quality standards, validation approaches, and issue remediation outcomes.

Key Responsibilities

• Data Quality Rule Design & Execution: Design, implement, and maintain automated and manual data quality rules to validate critical data elements used in models, dashboards, and regulatory or executive reporting. Define validation logic for accuracy, completeness, uniqueness, validity, consistency, and timeliness aligned to enterprise data standards. Partner with data engineering and analytics teams to embed data quality controls across data capture, data at rest, data movement, and data usage layers.
• Model & Analytics Data Validation: Perform independent validation of data inputs, transformations, and outputs supporting analytical and detection models. Assess data quality risks impacting model performance, explainability, and downstream decision-making. Establish ongoing monitoring metrics and thresholds to detect data drift, anomalies, and control breaks affecting models and analytics.
• Reporting & Downstream Data Assurance: Validate datasets used for regulatory, risk, finance, and management reporting, ensuring reported figures reconcile to authoritative sources. Support reporting owners by identifying data quality gaps, root causes, and remediation actions prior to publication. Provide data quality attestations, summaries, and insights to governance forums as required.
• Monitoring, Metrics & Issue Management: Develop and maintain data quality dashboards and KPIs that track rule performance, exceptions, and trends over time. Lead investigation of data quality issues, document findings, and drive remediation plans in partnership with data owners and custodians. Ensure data quality issues are logged, tracked, and resolved in accordance with enterprise data concern and remediation processes.
• Governance, Standards & Advisory: Act as a trusted advisor to business and technology teams on Enterprise Data Management Standard published by EDMO. Contribute to the evolution of enterprise data risk frameworks, policies, and best practices. Support audits, regulatory inquiries, and internal reviews by providing evidence of data quality controls and monitoring effectiveness.

Required Qualifications

• 7+ years of experience in data quality, data governance, data validation, analytics, or risk/data management roles. Experience in Insider Risk and/or Financial Crime Risk Management (FCRM) is an asset.
• Demonstrated experience in data profiling, designing and executing data quality rules and validation controls across complex data environments.
• Proven ability to support models, analytics, and reporting through strong data quality assurance practices.
• Must have strong coding experience in at least one of the following: Python, PySpark or SQL. Experience with Databricks, SSMS and/or reporting/EUC automation is an asset.
• Experience operating within enterprise data governance and control frameworks. Strong written and verbal communication skills, with the ability to explain complex data quality issues to both technical and non-technical audiences.