Data Quality Lead

General Summary The Data Quality Lead is responsible for defining and executing the enterprise data quality (DQ) strategy. This role ensures that data quality standards, rules, and monitoring processes are implemented effectively across all business domains. The individual will partner with Data Governance, IT, and business teams to oversee data quality measurement, issue management, and remediation. They will champion data quality excellence, mentor stakeholders, and drive maturity in data governance practices. Key Responsibilities (Percentages indicate approximate time allocation) 30% – Data Quality Strategy & Maturity Growth • Develop and implement the enterprise data quality strategy and roadmap. • Partner with data governance leadership to establish a data quality function. • Promote proactive, prevention-first data quality practices across the organization. 35% – Monitoring, Issue Management & Remediation • Lead enterprise data quality monitoring and issue resolution processes. • Coordinate triage, root cause analysis, and sustainable remediation efforts. • Design and maintain enterprise data quality dashboards and KPIs. • Partner with Business and IT to execute profiling, cleansing, and enrichment strategies. 35% – Standards & Rule Governance • Define and maintain enterprise data quality standards and policies. • Govern the lifecycle of data quality rules, ensuring alignment with business needs. • Validate and approve critical rule thresholds and controls. • Embed data quality checks into data product and system development processes. Job Complexity / Scope • Operates in a complex, cross-functional environment. • Influences adoption of new data quality processes and tools. • Communicates the value of data quality to both technical and business audiences. • Balances multiple priorities and projects with minimal supervision. • Comfortable working in evolving and ambiguous environments. Qualifications • Bachelor’s degree in Computer Science, Data Management, or related field. • Minimum 5 years of experience in data quality management or related discipline. • Hands-on experience with data profiling, rule creation, monitoring, and observability tools. • Knowledge of data catalog and governance tools (e.g., data.world preferred). • Understanding of master and reference data management concepts. • Strong analytical, problem-solving, and stakeholder engagement skills. • Excellent written and verbal communication abilities. • Proficient in Microsoft Office and BI tools (e.g., Power BI).