Key skills
Healthcare claims dataSQLSparkData modelingData quality auditingETL workflowsData transformationData lineage documentationMLETLData EngineeringAnalyticsCommunication
About this role
Machinify is a leading healthcare intelligence company with expertise across the payment continuum. They are seeking a skilled Senior Data Analyst to join their Data Engineering team to transform complex healthcare claims data into powerful insights that shape business strategy and support analytics initiatives.
Responsibilities:
- Design and maintain robust data transformations and mappings to convert raw medical claims into standardized canonical models
- Perform detailed data quality audits to detect, troubleshoot, and resolve issues impacting accuracy and completeness
- Write and optimize Spark SQL queries to validate data pipelines and support ongoing analytics
- Document data transformation logic and lineage to ensure transparency and reusability
- Collaborate cross-functionally with business stakeholders to translate data needs into technical specs
- Support onboarding of new client data feeds, ensuring smooth integration with minimal disruption
- Partner with data engineers to build and scale data pipelines, improving performance and reliability
- Act as a subject matter expert for healthcare claims data—advising on risk, trends, and business impact
- Work closely with data scientists to enable advanced analytics, ML models, and reporting use cases
- Troubleshoot ETL workflows and performance issues, driving continuous improvement in data architecture
Requirements:
- Bachelor's degree in Business, Computer Science, Health Informatics, or a related field
- 6+ years of experience as a data analyst or business analyst working with large datasets
- 6+ years of hands-on experience with healthcare claims data (e.g., 837 EDI, medical billing, encounter data)
- Advanced proficiency in SQL and familiarity working with Spark or similar big data framework will be bonus
- Solid understanding of data modeling concepts and best practices for analytics
- Proven problem-solving skills and attention to detail in complex data environments
- Strong organizational skills and ability to manage multiple concurrent initiatives
- Excellent written and verbal communication skills, especially when explaining technical concepts to non-technical stakeholders (e.g., clinicians, account managers, data scientists)
- Self-starter with a strong sense of ownership and accountability