Salary
≈ $70k – $169k per year (Estimated)
Location
Remote (United States)
Employment
Full-Time
Overview
Company
Impact
Profile match
About the Role
The Data Analyst plays a key role in monitoring, managing, and improving healthcare data file exchanges across clients, vendors, and internal systems. This role sits within a DataOps team responsible for ensuring data pipelines are accurate, reliable, and delivered on time.
You’ll work closely with teammates, engineering partners, and operational stakeholders to troubleshoot issues, support EDI workflows, and continuously improve data processes. The ideal candidate combines strong technical attention to detail with an understanding of how data operations support client satisfaction and broader business outcomes.
What You’ll Do
- Maintain a strong understanding of data and task workflows across operational departments.
- Communicate the status of ongoing tasks and issues to end users, team leads, and DataOps leadership.
- Analyze and troubleshoot insurance claims, eligibility, and import/export file mappings.
- Identify and resolve issues related to enrollment and enrollment changes within EDI files, partnering with engineering teams as needed.
- Coordinate ongoing EDI testing, implementations, and upgrades.
- Troubleshoot and report operational errors, including file movement and SFTP connection issues.
- Compare data files and reports against documented business requirements to ensure data quality and identify gaps.
- Support continuous improvement of data workflows, documentation, and operational processes.
- Perform additional duties as assigned by the Team Lead or DataOps Manager.
Requirements
What You Bring
- 4+ years of experience in system analysis, data analysis, and/or process improvement.
- 2+ years of experience in the healthcare industry; TPA experience preferred.
- Associate or Bachelor’s degree preferred, but not required.
- Strong analytical, critical thinking, and problem-solving skills.
- Intermediate to advanced proficiency in Microsoft Office (Excel, Outlook, Word).
- Familiarity with flat file data structures such as CSV or pipe-delimited files.
- Experience using data analysis tools such as Excel, SQL, Tableau, Power BI, or similar tools.
- Proven ability to analyze data, review requirements, and deliver insights that support business decisions.
- Strong collaboration and communication skills across technical and non-technical teams.
- Knowledge or experience with ANSI 5010 transactions (837, 835, 834, 270/271) preferred.
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