AI And DATA-Healthcare-Manager

Qualifications

• 812 years of experience in healthcare consulting, healthcare IT, data architecture, health informatics, data management, or digital transformation.

• Strong experience in data architecture and data modelling, including logical and physical data models.

• Experience designing enterprise data solutions within healthcare or another highly regulated industry.

• Experience integrating clinical, operational, administrative, structured, and unstructured data sources.

• Experience with healthcare interoperability standards, including HL7 v2 and FHIR, and with XML-based healthcare data formats.

• Experience with healthcare interface engines and interoperability platforms such as Mirth Connect, Rhapsody, Cloverleaf, InterSystems IRIS for Health, or equivalent integration suites.

• Experience designing data lakes, data warehouses, ETL/ELT frameworks, APIs, and data integration solutions.

• Experience working with cloud platforms such as Microsoft Azure, Amazon Web Services, or Google Cloud Platform.

• Experience with SQL and NoSQL databases.

• Experience in data governance, data quality, information management, and master data management.

• Understanding of healthcare analytics, advanced reporting, and AI-enabled data solutions.

• Knowledge of GDPR, healthcare data regulations, data privacy, data security, governance, and risk management considerations.

• Experience facilitating stakeholder workshops and translating business and clinical requirements into technical architecture and data solutions.

• Experience participating in or driving architecture discussions, technical solutioning, roadmap development, and implementation planning.

• Experience leading project workstreams and working with multidisciplinary business, clinical, and technology stakeholders.

• Experience guiding team members and reviewing architecture and technical deliverables.

• Experience working in Agile project environments.

• Educational background in Computer Science, Health Informatics, Information Systems, Engineering, Data Science, or a related field.