Job Summary:
The QA Data Analyst role focuses on ensuring the accuracy and integrity of benefits-related data, particularly census files. The ideal candidate will have strong analytical skills, working knowledge of Excel and data formats, and a background in benefits administration or a similar field. You will be responsible for validating client-submitted data, identifying errors, supporting onboarding processes, and auditing information against carrier rosters to prevent discrepancies.
Job type: Full-time
Benefits:
QA Data Analyst Key Responsibilities:
Troubleshoot and resolve EDI-related data issues, mapping errors, and formatting discrepancies.
Build custom imports, review and validate client-submitted census data against internal templates to ensure completeness and accuracy.
Check for missing required fields, formatting issues, and data inconsistencies within submitted files.
Provide constructive feedback to clients or internal teams when data files are incomplete, incorrectly formatted, or inconsistent.
Act as a subject matter expert and primary contact for census file inquiries during client onboarding and for ongoing file submissions.
Ensure client compliance with data submission guidelines and standardized templates.
Audit internal records against carrier invoices/rosters to identify and correct data mismatches.
Collaborate with cross-functional teams including implementation, benefits administration, and IT to resolve data quality issues.
Maintain thorough documentation of QA processes, issues encountered, and resolution steps.
QA Data Analyst Qualifications:
1+ years of experience in a QA, data analyst, or data operations role, preferably within benefits administration or healthcare data environments.
Proficiency in Microsoft Excel (e.g., VLOOKUP, pivot tables, basic formulas) for data comparison and validation tasks.
Strong logical thinking and problem-solving abilities, especially when working with structured data.
Basic coding knowledge (e.g., scripting for data handling) is a plus.
Excellent written and verbal communication skills; able to explain data issues clearly to technical and non-technical stakeholders.
Detail-oriented with a high level of accuracy in reviewing large datasets.
We are proud to be an equal opportunity employer. We provide equal employment opportunities to all employees and applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.