Data Governance and Automation Lead
6 days ago
The Data Governance and Automation Lead will be responsible for developing and enforcing data governance policies to ensure compliance with healthcare regulations and standards. This includes designing data quality frameworks for improving the accuracy, consistency, and security of healthcare data, as well as overseeing data integration across Electronic Health Records (EHRs), hospital management systems, and external data sources.
In addition, the Data Governance and Automation Lead will:
Digital Health Strategy & Innovation
- Lead the implementation of digital health solutions, including telemedicine, remote patient monitoring, and patient engagement platforms.
- Drive interoperability initiatives by integrating clinical and operational systems using HL7, FHIR, and other industry standards.
- Evaluate and adopt AI and machine learning technologies for predictive analytics in patient care and operational efficiencies.
- Optimize clinical workflows using digital tools to reduce administrative burden and enhance provider-patient interactions.
- Collaborate with clinicians and IT teams to design digital-first healthcare experiences that improve access to care.
Automation & Process Optimization
- Implement Robotic Process Automation (RPA) and AI-driven workflows to improve efficiency in administrative and clinical processes.
- Automate claims processing, medical coding, and billing workflows to enhance accuracy and reduce turnaround time.
- Deploy AI-powered chatbots and virtual assistants for patient engagement, scheduling, and support.
Requirements:
Bachelor's degree in health informatics, Data Science, Computer Science, Biomedical Engineering, or a related field.
10+ years of experience in healthcare IT, data management, or automation, preferably in a hospital or health tech setting.
Expertise in automation tools (UiPath, Blue Prism, Power Automate, Python-based RPA).
Experience working with cloud platforms (AWS, Azure, Google Cloud) for healthcare data storage and analytics.
Strong understanding of data engineering, ETL processes, SQL, NoSQL databases, and big data technologies (Hadoop, Spark).
Familiarity with cybersecurity best practices for securing patient data and healthcare applications.
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