Supervisor-Utilization Management

Maxicare Healthcare Corporation; Philippines; On-site; PHP 700,000 - 1,100,000; Full time

Job summary

Maxicare Healthcare Corporation seeks a Data Quality Lead to implement and maintain data quality standards across enterprise data in a healthcare context.

You will supervise data analysts, define QC rules, monitor KPIs, and collaborate with Data Engineering to automate checks. A strong background in SQL, ETL, Power BI, Python, and Oracle is preferred; healthcare data exposure is a plus.

Qualifications

• 1–3 years of relevant experience in data analytics or data quality, preferably with supervisory exposure.
• Hands-on experience in data profiling, validation, cleansing, reconciliation, and quality monitoring.
• Experience building data quality rules, KPIs, and reporting mechanisms.

Responsibilities

• Lead implementation and maintenance of data quality standards, policies, and controls.
• Establish data quality rules covering accuracy, completeness, and timeliness.
• Supervise data profiling, cleansing, reconciliation, and monitoring across sources.
• Analyze large datasets to identify data quality issues and risks.
• Monitor KPIs, dashboards, and reports; provide actionable recommendations.
• Coordinate root-cause analysis and corrective actions for data quality issues.
• Oversee data reconciliation between source systems and Oracle.
• Collaborate with Data Engineering to automate checks and monitoring.
• Define quality criteria for critical datasets and work with data owners.
• Identify opportunities to improve data processes and reduce manual work.

Skills

Data profiling

Data quality

Root-cause analysis

Team leadership

Tools

SQL

ETL/ELT

Power BI

Python

Oracle

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 .
• Supervise data profiling, validation, cleansing, reconciliation, and monitoring activities across multiple data sources.
• Analyze large and complex datasets to identify data quality issues, trends, anomalies, and potential risks.
• Monitor data quality KPIs, scorecards, dashboards, and management reports and provide actionable recommendations.
• Lead root-cause analysis and resolution of recurring data quality issues and coordinate corrective and preventive actions.
• Oversee data reconciliation and validation between 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 critical and gold-standard datasets.
• Work closely with data owners and business stakeholders to ensure data issues are resolved at the appropriate source.
• Identify opportunities to improve data processes, reduce manual activities, and increase data accuracy and efficiency.
• Supervise, coach, and develop Data Analysts, providing guidance on data analysis, quality assurance, and problem-solving.
• Prepare and present data quality findings, insights, and recommendations to management and relevant stakeholders.

Experience

• At least 1–3 years of relevant experience in data analytics, data quality, data management, master data management, or a related field, preferably with supervisory or team-lead experience.
• Hands‑on experience in data profiling, validation, cleansing, reconciliation, and data quality monitoring .
• Experience developing and implementing data quality rules, controls, KPIs, and reporting mechanisms.
• Experience working with large or complex datasets from multiple data sources.
• Experience conducting root‑cause analysis and resolving recurring data issues.
• Experience in data quality automation, process improvement, or data validation automation is highly preferred.
• Experience collaborating with Data Engineering, IT, business, and other cross‑functional teams.
• Experience in the healthcare industry or healthcare‑related data is an advantage.

Preferred Technical Skills

• Proficiency in SQL and data querying.
• Knowledge of ETL/ELT processes and data integration concepts .
• Advanced skills in data profiling, validation, reconciliation, and analysis.
• Experience with data quality tools, automation, and monitoring solutions.
• Knowledge of data governance, master data management, and data quality frameworks .
• Experience with Power BI or similar data visualization and reporting tools .
• Experience with Python or other scripting languages for data analysis and automation.
• Knowledge of data modeling, metadata, data lineage, and data standards.
• Familiarity with Oracle and enterprise data systems.
• Familiarity with healthcare data is an advantage.