Remote Healthcare Data Quality Lead

Highmark Health

Yuma (AZ)

Remote

USD 73.000 - 117.000

Vollzeit

Vor 6 Tagen
Sei unter den ersten Bewerbenden

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

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Zusammenfassung

Highmark Health seeks an experienced Quality Lead to define data-testing strategy and oversee end-to-end quality across healthcare data flows. The role emphasizes leadership of technical teams and strategic risk management rather than day-to-day hands-on testing.

The ideal candidate will translate complex data-quality risks into clear business impacts for executives while guiding cross-functional collaboration and ensuring release readiness in a remote setting.

Qualifikationen

  • 3+ years of ability to manage projects, timelines and resources
  • 3+ years of excellent customer service and client satisfaction
  • 3+ years of leading and mentoring QA teams through SDLC phases, coaching testers

Aufgaben

  • Define data testing strategy, planning, estimation, execution oversight, metrics, and reporting
  • Oversee SQL/database validation, ETL, migration, and end-to-end data-flow testing
  • Guide test data management, automation, and data-validation tooling
  • Understand claims, membership, provider, and care management data in healthcare
  • Lead risk identification, mitigation, defect management, and root cause analysis
  • Drive quality across SDLC, Agile delivery, and release readiness
  • Communicate quality status and business impact to executives and clients

Kenntnisse

Project management
Team leadership
Quality assurance
Data testing
Healthcare data domain

Ausbildung

Bachelor's degree in Computer Science/Information Technology

Tools

Oracle
SQL Server
DB2
Snowflake
Databricks
Splunk
Dynatrace

Jobbeschreibung

Highmark Health seeks an experienced Quality Lead to define data-testing strategy and oversee end-to-end quality across healthcare data flows. The role emphasizes leadership of technical teams and strategic risk management rather than day-to-day hands-on testing.

The ideal candidate will translate complex data-quality risks into clear business impacts for executives while guiding cross-functional collaboration and ensuring release readiness in a remote setting.

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