About the role

Data Quality & Governance Specialist at Alberta Blue Cross establishing data quality standards and frameworks. Collaborating with stakeholders to execute a data quality program aligned with audit requirements.

Responsibilities

Help Develop a Data Quality Framework: create data quality principles, dimensions, and roles, and collaborate with stakeholders across business and IT to gain alignment and approval.
Create Data Quality Standards: draft and publish the data quality standards needed to support governance, audit, and compliance requirements.
Define Critical Data Elements (CDEs) & Quality Rules: establish processes for identifying and approving CDEs, conduct data profiling, and translate known issues and business rules into clear, actionable data quality rules.
Support Automated Data Quality Validations: partner with data engineers to convert quality rules into automated validation checks, reconciliation logic, and monitor workflows.
Establish Data Quality Issue & Remediation Management: define data quality issue reporting and resolution processes, create supporting templates and workflows, and establish remediation procedures, approval gates, and controls for governed data corrections.
Stakeholder Change Management: partner with OCM to communicate and train impacted stakeholders on new responsibilities and process changes.
Build Team Alignment & Partnerships: work with business and IT teams to help them understand data quality expectations, adopt required process changes, and collaborate toward a unified, organization wide data quality vision.

A post-secondary degree or diploma in Information Management, Business, Computer Science, Data Science or a related field; equivalent experience will be considered.
10+ years of experience in data quality, data governance, data management, or related roles.
Data quality or governance certifications (e.g., CDMP, IQCP) are considered an asset.
Experience establishing data quality frameworks, standards, and governance processes.
Strong understanding of data quality dimensions, rule creation, CDE identification, data profiling, data issue and remediation management, and data lifecycle management.
Familiarity with modern data platforms (e.g., Databricks, cloud environments) and the ability to translate business logic into implementable data quality rules.
Exceptional collaboration and facilitation skills, with the ability to work effectively across teams to help them understand upcoming changes, adopt new processes, and align their work to enterprise data quality goals.
Ability to quickly understand current processes, identify where improvements or changes are needed, and guide disparate teams toward a unified approach.
Excellent written and verbal communication skills, with the ability to train and support diverse audiences.
Highly organized, analytical, and detail-oriented, able to manage multiple priorities and deliver under tight timelines.
A proactive, curious mindset, with the ability to work both independently and collaboratively.