Data Governance Specialist

As a Data Quality Specialist, your role will involve defining and measuring data quality metrics to ensure accuracy, completeness, validity, consistency, timeliness, and reliability. You will be responsible for continuously monitoring data quality, conducting audits, performing root cause analysis for recurring data issues, and implementing preventive measures and remediation plans. Additionally, you will develop and maintain comprehensive data profiles to understand data characteristics, create and implement validation rules, and design data cleansing processes to enhance overall data quality and reliability. In terms of Data Governance, you will establish and enforce data governance practices to ensure compliance with regulatory requirements and corporate policies. This includes developing and maintaining a comprehensive metadata repository, collaborating with business users to identify data needs, pain points, and requirements, and continuously seeking opportunities for process improvement in data governance and quality management. You will also work on understanding user roles and access requirements for systems, implementing row-level security for analytical solutions, and establishing naming conventions and synonyms to ensure data accessibility and readability. Moreover, you will be responsible for establishing KPIs for data governance and quality efforts, creating regular reports for stakeholders to track progress, and demonstrating the value of data governance initiatives. Additionally, you will set up a feedback loop where users can report data quality issues and suggest improvements for continuous improvement. Qualifications Required: - Strong understanding of data quality metrics and data profiling techniques - Experience in data validation, data cleansing, and metadata management - Knowledge of data governance practices and regulatory requirements - Ability to collaborate with business users and stakeholders to identify data needs and requirements - Proficiency in establishing naming conventions, synonyms, and row-level security for analytical solutions Company Details: The company emphasizes continuous improvement in data governance and quality management through establishing feedback loops for user input and implementing preventive measures for recurring data issues. Additionally, the company prioritizes collaboration with business users and stakeholders to ensure data is fit for its intended use and regularly tracks progress through KPIs and stakeholder reports.,