Data Analyst/ETL Developer (remote)

At Claritev, we pride ourselves on being a dynamic team of innovative professionals. Our purpose is simple - we strive to bend the cost curve in healthcare for all. Our dedication to service excellence extends to all our stakeholders - internal and external - driving us to consistently exceed expectations. We are intentionally bold, we foster innovation, we nurture accountability, we champion diversity, and empower each other to illuminate our collective potential.

Be part of our amazing transformational journey as we optimize the opportunity towards becoming a leading technology, data, and innovation voice in healthcare. Onward and Upward!!!

JOB SUMMARY:

The Data Analyst/ETL Developer plays a crucial role in providing insights for decision making. The Data Analyst transforms data into usable metrics through data processing software and business development strategies to provide valuable insights to company stakeholders.

JOB ROLES AND RESPONSIBILITIES:

• Utilize SQL, and/or Python in data analytics to collect, understand, transform, cleanse, store, and share data in a privacy-preserving way.
• Debug mappings and identify errors and error rows so that they can be corrected and re-loaded into a target system.
• Review and analyze functional requirements and mapping documents.
• Develop, maintain, and support ETL data pipelines for healthcare products and analytics platforms.
• Initialize and configure data sites/environments to enable downstream analytics and reporting by partner teams.
• Collaborate with upstream and downstream teams to ensure successful site onboarding, handoff, and readiness.
• Monitor ETL jobs and pipelines in production, identifying failures, performance degradation, and data anomalies.
• Troubleshoot and resolve production issues in ETL workflows, including failed loads, data mismatches, and processing delays.
• Perform root cause analysis for pipeline incidents and implement corrective and preventive fixes.
• Validate incoming healthcare datasets prior to release for downstream consumption.
• Build and maintain data validations to ensure:

1. source to target reconciliation
2. row counts and completeness
3. business rule enforcement
4. data type, format, and constraint integrity