Data Quality Analyst I - Miamisburg - IS Analytic Health - Full Time - Days at Kettering Health

Kettering Health is a not-for-profit system of 13 medical centers and more than 120 outpatient facilities serving southwest Ohio. We are committed to transforming the health care experience with high-quality care for every stage of life. Our service-oriented mission is in action every day, whether it’s by providing care in our facilities, training the next generation of health care professionals, or serving others through international outreach.

The Data Quality Analyst is responsible for ensuring the accuracy, consistency, and reliability of organizational data. This role involves analyzing data sources, identifying/resolving quality issues, supporting data governance activities, and collaborating with stakeholders to support effective decision-making through highquality data.

Job Requirements:

 Associates degree or equivalent combination of education, certification, and experience.

• 0-2 years of experience in data analysis, report creation and visualization or related field. Required Skills

• Epic Certification or obtained within 6 months.

• Experience with business intelligence tools (e.g., Power BI, Tableau, Qlik), Data Analytics, Information management, Computer Science, or related fields.

• Knowledge of master data management (MDM) concepts.

• Prior experience working in healthcare industry with Epic EMR

• Knowledge of data governance principles and regulatory requirements (e.g., HIPAA, GDPR, if applicable).

• Strong analytical and problem-solving skills with attention to detail.

Job Responsibilities:

• Work closely with data owners, business analysts, and IT teams to resolve data quality issues.

• Document data quality rules, definitions, and standards.

• Support data governance initiatives by ensuring compliance with organizational and regulatory requirements.

• Create dashboards and reports to communicate data quality metrics and trends to stakeholders and data stewards.

• Assist in root cause analysis for recurring data issues and propose sustainable solutions.

• Collaborate with project teams to ensure new systems and integrations meet data quality standards.

• Provide training and guidance on best practices for data entry, management, and stewardship.