Data Quality and Governance Product Manager - Regional Business Intelligence & Planning

Overview

We are seeking a Data Quality and Governance Product Manager who will own the strategic planning and execution of data governance programs across regional data marts and metric repositories. The role involves maintaining a unified business glossary and metric taxonomy to ensure consistent definitions across finance, commercial, and data science teams.

Key Responsibilities

• Develop and maintain the product strategy and delivery roadmap for data governance initiatives impacting regional data resources.
• Create and manage a centralized glossary of business terms and metric classifications to guarantee consistent use among various teams.
• Implement data quality frameworks such as anomaly detection, data lineage tracking, and service level agreement (SLA) monitoring in collaboration with data engineering groups.
• Convert changing business and regulatory requirements into clear governance policies and corresponding data model modifications.
• Lead collaborative sessions among finance, compliance, regional market leaders, and machine learning teams to align data standards and resolve discrepancies.
• Conduct proactive audits of metric logic and data pipelines to catch and address inconsistencies before they affect reports or model outcomes.
• Manage multiple stakeholder demands, balancing the need for rigorous governance with efficient delivery timelines.

Qualifications

• Bachelor’s degree in any field is required; having a master’s degree is preferred but not mandatory.
• A minimum of two years’ full-time experience in technical product management, covering complete product lifecycle.
• Competency in SQL and Python programming languages.
• Proven track record managing the end-to-end delivery of technical products, from concept to launch and iterative improvement.
• Excellent communication skills with the ability to foster consensus between technical teams and business units across various regions, including familiarity with regional stakeholder management and engineering collaboration.
• Strong analytical skills to interpret complex and unclear business requirements into well-defined data definitions and technical criteria.
• Meticulous attention to detail paired with a methodical process for detecting and solving data quality challenges.