Data Management Lead

About the Role

Employment Type: Full time

Become a part of our caring community and help us put health first. The primary responsibility of the Data Governance Data Lead at Humana Military is to lead the design, implementation, and continuous improvement of Master Data Management (MDM) and Reference Data Management (RDM) best practices, initially focusing on provider and beneficiary data with the expectation that additional data domains may be included as organizational needs evolve.

A significant aspect of the role is to provide comprehensive data management support to the data science team, including tasks related to SQL, data transformations, and data movement to enable reliable analytics and data-driven initiatives. The role requires hands-on experience with modern data engineering, including automation of data pipelines (utilizing tools such as Python and SQL), development of end-to-end automated solutions with traceability and monitoring, and experience working in both cloud (Azure, AWS, GCP) and on-premises (Windows) environments.

The position will collaborate closely with data scientists and apply expertise to healthcare data, real-time data pipelines, and innovative technologies such as GenAI and Python-based UI applications. Additionally, the position is responsible for advancing data quality and promoting process automation, ensuring that essential data assets are accurate, consistent, and efficiently maintained to support operational excellence and scalability. Humana Military offers a supportive environment for professional growth, valuing contributions that enhance healthcare data management and outcomes.

Key Accountabilities

• Lead the design, implementation, and oversight of master data management (MDM) and reference data management (RDM) initiatives as the primary responsibility, while also contributing to the development, implementation, enforcement, and continuous improvement of the organization’s data governance framework.
• Provide data management support to the Data Science team, including data preparation, integration, and quality management, and enablement of robust analytics and scalable data operations.
• Collaborate with data scientists to develop and optimize automated, end-to-end data pipelines, ensuring traceability, monitoring, and automation throughout the data lifecycle, using tools such as Python and SQL.
• Drive initiatives to monitor, assess, and remediate data quality issues, ensuring compliance with regulatory requirements and organizational standards.
• Develop automated solutions and leverage real-time data streaming technologies where appropriate.
• Collaborate with cross-functional stakeholders, including IT and business units, to identify enterprise data requirements and implement scalable, data-driven solutions.
• Utilize both cloud (Azure, AWS, GCP) and on-premises (Windows) platforms.
• Apply best practices for healthcare data, support real-time data processing, and contribute to the development of GenAI and UI applications.
• Promote a culture of data stewardship, accountability, and continuous improvement throughout the organization.
• Use your skills to make an impact.

Required Qualifications

• Our Department of Defense contract requires U.S. Citizenship.
• Successfully receive interim approval for government security clearance (NBIS - National Background Investigation Services).
• HGB is not authorized to do work in Puerto Rico per our government contract.
• We are not able to hire candidates that are currently living in Puerto Rico.
• Bachelor's degree
• 5 years of experience in MDM/RDM, data governance, or data management roles.
• 5 years of experience in healthcare/provider data, business, or financial services – with data management or data governance.
• Strong knowledge of data governance policies, metadata management, and compliance.
• Experience developing components using Python, and SQL, for data pipeline automation (storage, processing, retrieval).
• Experience building fully automated, end-to-end data pipeline solutions with traceabil.