Data Quality Supervisor
Data Quality Supervisor
maxicare healthcare corporation1-3 Years
- Posted 23 hours ago
- Be among the first 10 applicants
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.
- 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.
- 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 .
More Info
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Key Skills
KPIs and reporting
data quality automation
automation and monitoring solutions
data quality tools
root-cause analysis
ETL/ELT processes
Python or other scripting languages
data quality monitoring
About Company