Data Quality Supervisor

Maxicare Healthcare Corporation; Philippines; On-site; PHP 450,000 - 750,000; Full time

Job summary

Maxicare Healthcare Corporation is seeking a Data Quality Lead in the Philippines to implement and maintain data quality standards, policies, and controls across critical enterprise data and provider data. You will establish data quality rules, monitor KPIs and dashboards (Power BI), lead root-cause analyses, coach analysts, and collaborate with data engineering to automate checks and improve processes.

This role requires 1–3 years of data quality experience and strong communication to drive

Qualifications

• Experience implementing data quality principles and governance.
• Ability to lead data quality initiatives and coach analysts.
• Experience with large, multi-source datasets and dashboards.

Responsibilities

• Lead the implementation and maintenance of data quality standards and controls.
• Establish and maintain data quality rules, validation criteria, and KPIs.
• Oversee data profiling, assessment, validation, and monitoring of provider data.
• Monitor data quality performance via dashboards and reports.
• Drive root-cause analysis and corrective actions for data quality issues.
• Collaborate with Data Engineering to automate checks and monitoring.
• Coach Data Quality Analysts and promote continuous improvement.
• Ensure datasets meet established data standards and gold-quality data.
• Partner with data owners to resolve issues at the source.
• Oversee data reconciliation across sources including Oracle.

Skills

Data governance

Data quality

Data profiling

Data reconciliation

Leadership

Communication

Tools

Power BI

Python

ETL/ELT

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 .