At Globe, our goal is to create a wonderful world for our people, business, and nation. By uniting people of passion who believe they can make a difference, we are confident that we can achieve this goal.

Job Description The Data Quality Manager is key in proactively ensuring that data quality is maintained across the enterprise, and as a result enables the Analytics Team to deliver relevant and accurate models and insights. He/She will also drive action within the enterprise to ensure that data issues are resolved.

DUTIES AND RESPONSIBILITIES:

Establish data quality objectives aligned with Data Governance Policies

Devises and executes proper data collection procedures, policies, guidelines including data cleaning, standardization, and analysis

Define, Track and Manage Data Quality KPIs across the enterprise

Implement controls and compliance metrics to reduce data issues and improve data quality 

Develops evaluation methods and conduct constant testing and experimentation to provide the Data Governance Council with feedback and recommendations for improvements in data management and governance process, standards and guidelines

Design processes and relevant trainings as well as lead initiatives to ensure alignment of different data owners to data quality objectives and plans

Partner with the Data Governance Council to define and align data management and governance strategies while providing key inputs from the data quality and cleansing initiatives 

Collaborates with reporting, analytics, and operational segments to ensure data quality standards are met, errors and root causes identified

Identify, prioritize and lead Enterprise-wide data cleansing initiatives to deliver substantial improvements in data quality across the enterprise

Plan, manage and deliver communication about the data cleanse activity to the key stakeholders throughout the process.

Manage and drive teams to run and deliver initiatives designed to resolve data quality issues

Manage project risks and issues and manage stakeholder’s expectations on initiatives started

Mentor team members and provide training as needed

KPIs:

Data Quality Index (DQI): Assess the overall quality of data across the enterprise, considering factors such as accuracy, completeness, consistency, and timeliness.

Data Issue Resolution Time: Monitor the time taken to identify and resolve data quality issues reported by various stakeholders.

Compliance with Data Governance Policies: Ensure adherence to established data governance policies and procedures, including alignment of data quality objectives with governance policies.

Data Cleansing Effectiveness: Evaluate the effectiveness of data cleansing initiatives by measuring the reduction in data errors and inconsistencies.

Stakeholder Satisfaction:Measure stakeholder satisfaction with data quality improvements and initiatives through regular surveys or feedback sessions.

TOP 3-5 DELIVERABLES:

Data Quality Objectives:Establish and communicate data quality objectives aligned with Data Governance Policies, ensuring that they are clearly defined, measurable, and achievable.

Data Collection Procedures and Policies:Develop and execute proper data collection procedures, policies, and guidelines, encompassing data cleaning, standardization, and analysis to ensure high-quality data inputs for analytics and reporting purposes.

Data Quality KPI Management: Define, track, and manage Data Quality Key Performance Indicators (KPIs) across the enterprise, monitoring data quality metrics and performance against established benchmarks.

Controls and Compliance Metrics Implementation:Implement controls and compliance metrics to identify, mitigate, and reduce data issues, ensuring continuous improvement in data quality standards and compliance with regulatory requirements.

Enterprise-wide Data Cleansing Initiatives: Identify, prioritize, and lead enterprise-wide data cleansing initiatives aimed at delivering substantial improvements in data quality across systems and processes, addressing data errors, inconsistencies, and redundancies.

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