Data Quality Supervisor

Maxicare Healthcare Corporation; Makati; On-site; PHP 480,000 - 900,000; Full time

Job summary

Maxicare Healthcare Corporation is seeking a Data Quality Lead to establish and enforce data quality standards across enterprise data, with a focus on governance, profiling, validation, and reconciliation. The role requires strong leadership to supervise and develop analysts while driving continuous improvement and automating checks.

Responsibilities include monitoring KPIs, partnering with Data Engineering, and ensuring high-quality provider data across source systems and Oracle, with a

Qualifications

• Strong knowledge of data quality principles, data governance, and master data management.
• Advanced skills in profiling, validation, reconciliation, and analysis.
• Familiarity with data modeling, metadata, data lineage, and data standards.
• Proficiency in Python or other scripting languages for data quality automation is preferred.
• Experience with data quality tools and monitoring solutions is a plus.

Responsibilities

• Lead the implementation and maintenance of data quality standards, policies, procedures, and controls for critical enterprise data.
• Establish and maintain data quality rules and validation criteria covering accuracy, completeness, consistency, uniqueness, validity, and timeliness.
• Oversee data profiling, assessment, validation, and monitoring of critical provider data.
• Monitor and report data quality performance through KPIs, scorecards, dashboards, and management reports.
• Lead the investigation and resolution of data quality issues through root-cause analysis and corrective/preventive actions.
• Oversee data reconciliation and validation across source systems, standardized datasets, and Oracle.
• Collaborate with Data Engineering teams to automate data quality checks, validation, reconciliation, and monitoring processes.
• Define and monitor quality criteria for gold-standard data and ensure critical datasets meet established standards.
• Partner with data owners and cross-functional teams to resolve data quality issues at the appropriate source.
• Supervise, coach, and develop Data Quality Analysts while driving continuous improvement and reducing manual quality activities.

Skills

Data quality principles

Data governance

Master data management

Data profiling

Validation

Reconciliation

Analysis

Leadership

Communication

Collaboration

Data accuracy

Ownership and accountability

Tools

Power BI

ETL/ELT

Python

Data quality tools

Data visualization

Job description

Job Description:

Key Responsibilities

• Lead the implementation and maintenance of data quality standards, policies, procedures, and controls for critical enterprise data.
• Establish and maintain data quality rules and validation criteria covering accuracy, completeness, consistency, uniqueness, validity, and timeliness.
• Oversee data profiling, assessment, validation, and monitoring of critical provider data.
• Monitor and report data quality performance through KPIs, scorecards, dashboards, and management reports.
• Lead the investigation and resolution of data quality issues through root-cause analysis and corrective/preventive actions.
• Oversee data reconciliation and validation across source systems, standardized datasets, and Oracle.
• Collaborate with Data Engineering teams to automate data quality checks, validation, reconciliation, and monitoring processes.
• Define and monitor quality criteria for gold-standard data and ensure critical datasets meet established standards.
• Partner with data owners and cross-functional teams to resolve data quality issues at the appropriate source.
• Supervise, coach, and develop Data Quality Analysts while driving continuous improvement and reducing manual quality activities.

Required Experience

• 1–3 years of experience in data quality, data management, data analytics, master data management, or a related field.
• Hands-on experience in data profiling, validation, cleansing, reconciliation, and data quality monitoring.
• Experience developing and implementing data quality rules, controls, KPIs, and reporting.
• Experience working with large or complex datasets from multiple data sources.
• Experience conducting root-cause analysis and resolving recurring data quality issues.
• Experience in data quality automation or process improvement is highly preferred.
• Experience working with ETL/ELT processes and data integration is preferred.
• Experience using data visualization and reporting tools, such as Power BI or similar platforms, is an advantage.

Qualifications & Skills

• Strong knowledge of data quality principles, data governance, and master data management.
• Advanced skills in data profiling, validation, reconciliation, and analysis.
• Knowledge of data modeling, metadata, data lineage, and data standards.
• Proficiency in Python or other scripting languages for data quality automation is preferred.
• Familiarity with data quality tools, automation, and monitoring solutions.
• Familiarity with healthcare data is an advantage.
• Strong analytical and problem-solving skills, with the ability to identify issues and determine root causes.
• Strong leadership skills with the ability to supervise, coach, and develop team members.
• Excellent communication and collaboration skills across teams and functions.
• Strong attention to data accuracy, integrity, and quality.
• Proactive mindset with a focus on continuous improvement and process optimization.
• Ability to translate data quality issues and insights into clear recommendations and business actions.
• Strong sense of ownership and accountability for quality outcomes and issue resolution.