Data Engineer

MAIN PURPOSE OF JOB

• To build, run and improve the data pipelines, enterprise data models and governed data products that feed reporting, analytics and AI at Mediclinic Middle East.
• To deliver the data for the Operational Excellence workstream to agreed standards of quality, timeliness and security, working to the architecture and engineering standards set by the Lead Data Architect: automated measurement of process KPIs in place of manual collection, the data layer behind the Operations Command Centre, and the data on which certified baselines and benefit evidence rest.

KEY RESPONSIBILITY AREAS

• Build and maintain reliable data pipelines and enterprise data models for the Operational Excellence workstream
• Deliver governed data products through the Denodo access layer for reporting, the command centre and AI use cases
• Ensure the quality, security and integrity of the data that baselines and benefits rest on
• Work to engineering standards, document the work and support colleagues and data consumers

REQUIRED EDUCATION

ESSENTIAL EDUCATION

• Bachelor’s degree in Computer Science, Information Systems, Engineering or a related field

DESIRED EDUCATION

• Certification in InterSystems IRIS, Denodo or Microsoft Azure data engineering

REQUIRED EXPERIENCE

ESSENTIAL MINIMUM EXPERIENCE

• Minimum 3 years of experience in data engineering, ETL or database development

DESIRED EXPERIENCE

• More than 5 years in data engineering
• Healthcare data (EHR, claims or clinical coding) and data virtualisation or healthcare data platforms
• Real-time or near-real-time data feeds for operational dashboards and alerting

REQUIRED JOB SKILLS AND KNOWLEDGE

• InterSystems IRIS for Health, HealthShare or a comparable healthcare data platform
• Data virtualisation development
• Cloudshare and university security systems, including authentication, authorizstion, and data security
• Cloud & hybrid networking (e.g., Azure/AWS connectivity patterns, private connectivity, DNS, routing)
• Cloud Database Exposure (Azure/AWS)
• Cloud MS Azure, Cloud Architecture
• Cloud Security (Azure Security Center, Microsoft Defender)
• Data Science, Data Engineering, Analytical Methods (e.g., Statistics, Machine Learning, Artificial Intelligence)
• Evaluation of digital health, health technology and innovation, artificial intelligence, machine learning
• Analysis, interpretation, and presentation of healthcare data and information
• Applied data analytics within a healthcare environment
• Agile Development Methodologies
• Process knowledge (BPMN 2.0, KPI and SLA frameworks) sufficient to turn process definitions into data