Data Quality Analyst

Responsibilities:

• Perform data quality validation across RCM datasets, including Charges, Payments, Adjustments, Denials, and Accounts Receivable (A/R).
• Conduct transaction-level reconciliation between PMS/EHR systems and downstream systems.
• Identify and resolve data discrepancies, missing data, and inconsistencies.
• Develop and execute SQL queries for data validation and root cause analysis.
• Validate data transformations, mappings, and business rules.
• Perform trend analysis and anomaly detection on key RCM metrics, including Denial Rate, A/R Days, and Collections.
• Collaborate with cross-functional teams to define validation rules and acceptance criteria.
• Maintain data quality dashboards, validation logs, and audit trails.
• Support client onboarding and data validation cycles.
• Document data issues, root cause analysis (RCA), and remediation steps.
• Build reusable SQL-based validation scripts and frameworks for scalable data quality assurance (DQA).

Requirements:

• 4-8 years of experience in data QA or data validation, preferably in the healthcare RCM domain.
• Strong understanding of RCM workflows, including billing, coding, payments, denials, and accounts receivable.
• Hands-on expertise in SQL, including joins, aggregations, validation queries, and performance tuning.
• Experience working with large-scale, transaction-level healthcare datasets.
• Strong analytical, problem-solving, and attention-to-detail skills.
• Experience with ETL testing, data validation frameworks, or data QA processes.
• Ability to interpret business metrics and translate them into data validation logic.
• Understanding of HIPAA compliance and healthcare data security standards.

Nice to Have:

• Experience with data warehousing or data lake environments with AWS.
• Familiarity with Athena, Redshift, Snowflake, or similar technologies.
• Exposure to data quality tools.

Skills

healthcare, rcm, revenue cycle, sql