Data Quality Manager

Overview

Data Quality Lead

Data Quality & Kpi Assurance

• Lead validation of KPIs, metrics, business rules, and analytical outputs across dashboards and reports.
• Ensure consistency of calculations, definitions, and results across multiple platforms and reporting layers.
• Validate alignment between business requirements, data models, and analytics outputs.
• Perform functional and cross-platform validation of reporting and analytical products.

Governance & Quality Oversight

• Define and enforce enterprise-wide data quality standards, controls, and validation frameworks.
• Review and approve data quality rules, testing approaches, and validation methodologies.
• Act as the final quality authority prior to executive and leadership reporting releases.
• Drive continuous improvement of data quality processes and controls.

Stakeholder & Vendor Management

• Partner with business stakeholders to clarify KPI definitions, business rules, and reporting expectations.
• Oversee quality assurance of externally delivered datasets, dashboards, and analytics products.
• Manage critical data quality issues, escalations, and remediation activities.
• Provide guidance on data quality impacts during platform enhancements and transformations.

Strategy & Data Governance

• Monitor and report on data quality performance across platforms.
• Identify systemic data issues and recommend strategic improvements.
• Contribute to data governance, metadata, reference data, and master data initiatives.
• Mentor and guide Data Quality Analysts and Data Quality Developers.

Required Experience

• 8–10+ years of experience in Data Quality, Data Governance, Analytics Assurance, or related fields.
• Strong experience validating KPIs, metrics, dashboards, and analytical outputs.
• Experience working with senior stakeholders and leadership-facing reporting environments.
• Proven ability to lead data quality initiatives across enterprise-scale data ecosystems.

Technical Skills

• Strong understanding of data models, data warehousing, ETL/ELT processes, and analytics pipelines.
• Ability to review SQL queries, transformation logic, and validation frameworks.
• Experience overseeing dashboard, reporting, and analytics quality assurance.
• Familiarity with metadata management, data governance, ontology, and business glossary concepts.