About the Job

The MEL & Digital Health Systems Manager is responsible for the design, development, and optimization of ICRHK’s data ecosystem to support high-quality programme monitoring, research, and organizational learning. This role sits at the intersection of monitoring and evaluation, digital health, and data engineering. It will ensure that ICRHK has robust, scalable, and integrated systems that enable efficient data collection, real-time analytics, and evidence-based decision-making across all programmes. The role is critical to transitioning the organization from fragmented, project-based data systems to a cohesive, interoperable, and future-ready data architecture.

Duties & Responsibilities

MEL Systems Design & Management

• Lead the design, development, and continuous improvement of digital MEL systems across programmes and research projects
• Translate programme and research requirements into functional system specifications and user-friendly data solutions
• Oversee configuration and deployment of digital data collection tools (e.g., mobile-based platforms, electronic registries)
• Ensure systems are scalable, adaptable, and aligned with evolving programme needs

Data Architecture & Infrastructure Development

• Design and maintain integrated data architecture that connects multiple data sources, including programme, research, and administrative systems
• Develop and manage centralized databases and data warehouses to support efficient storage, retrieval, and analysis of data
• Establish data pipelines and workflows to automate data ingestion, cleaning, validation, and reporting processes
• Ensure optimal system performance, reliability, and documentation of data structures and processes

Data Integration & Interoperability

• Ensure interoperability between different platforms and systems (e.g., MEL tools, national health information systems, research databases)
• Develop and implement APIs and integration protocols where required
• Support alignment with national and global digital health standards and frameworks
• Facilitate seamless data exchange across internal teams and external stakeholders

Data Analytics, Visualization & Use

• Lead the development of interactive dashboards, data visualization tools, and automated reporting systems for internal and external use
• Support advanced analytics by ensuring data is structured and accessible for statistical analysis and modelling
• Collaborate closely with the Statistician/Epidemiologist to enable high-quality data analysis
• Promote a culture of data use by ensuring systems generate actionable, user-friendly insights

Data Quality, Security & Governance

• Establish and enforce data quality assurance mechanisms, including validation rules, routine audits, and data cleaning protocols
• Develop and implement data governance frameworks, including data standards, access controls, and user permissions
• Ensure compliance with data protection regulations, ethical standards, and organizational policies
• Strengthen data backup, recovery, and cybersecurity measures

Capacity Building & Technical Support

• Provide ongoing technical support to programme and research teams in the use of MEL systems and digital tools
• Develop user guides, standard operating procedures (SOPs), and training materials
• Conduct training sessions to enhance staff capacity in data collection, management, and use
• Serve as the internal focal point for troubleshooting system issues and driving continuous improvement

Innovation & Digital Transformation

• Identify and introduce innovative technologies and tools to enhance data systems and workflows
• Support the adoption of digital health solutions and emerging technologies (e.g., cloud platforms, mobile data systems, AI-enabled analytics where appropriate)
• Contribute to organizational digital transformation initiatives and long-term data strategy
• Keep abreast of global best practices in MEL systems, data engineering, and digital health

Personal Attributes

• Additional training or certification in digital health, health information system, enterprise system or data system is an added advantage
• Minimum of 5–8 years of progressive experience in MEL systems, database design, digital health systems, or data engineering within the development or health sector
• Demonstrated experience designing and implementing end-to-end data systems and architectures
• Experience working with multi-donor programmes and complex data environments especially in Sexual and Reproductive Health is highly desirable
• Proven ability to translate technical concepts into practical solutions for non-technical users

• Lead the design, development, and continuous improvement of digital MEL systems across programmes and research projects
• Translate programme and research requirements into functional system specifications and user-friendly data solutions
• Oversee configuration and deployment of digital data collection tools (e.g., mobile-based platforms, electronic registries)
• Ensure systems are scalable, adaptable, and aligned with evolving programme needs
• Design and maintain integrated data architecture that connects multiple data sources, including programme, research, and administrative systems
• Develop and manage centralized databases and data warehouses to support efficient storage, retrieval, and analysis of data
• Establish data pipelines and workflows to automate data ingestion, cleaning, validation, and reporting processes
• Ensure optimal system performance, reliability, and documentation of data structures and processes
• Ensure interoperability between different platforms and systems (e.g., MEL tools, national health information systems, research databases)
• Develop and implement APIs and integration protocols where required
• Support alignment with national and global digital health standards and frameworks
• Facilitate seamless data exchange across internal teams and external stakeholders
• Lead the development of interactive dashboards, data visualization tools, and automated reporting systems for internal and external use
• Support advanced analytics by ensuring data is structured and accessible for statistical analysis and modelling
• Collaborate closely with the Statistician/Epidemiologist to enable high-quality data analysis
• Promote a culture of data use by ensuring systems generate actionable, user-friendly insights
• Establish and enforce data quality assurance mechanisms, including validation rules, routine audits, and data cleaning protocols
• Develop and implement data governance frameworks, including data standards, access controls, and user permissions
• Ensure compliance with data protection regulations, ethical standards, and organizational policies
• Strengthen data backup, recovery, and cybersecurity measures
• Provide ongoing technical support to programme and research teams in the use of MEL systems and digital tools
• Develop user guides, standard operating procedures (SOPs), and training materials
• Conduct training sessions to enhance staff capacity in data collection, management, and use
• Serve as the internal focal point for troubleshooting system issues and driving continuous improvement
• Identify and introduce innovative technologies and tools to enhance data systems and workflows
• Support the adoption of digital health solutions and emerging technologies (e.g., cloud platforms, mobile data systems, AI-enabled analytics where appropriate)
• Contribute to organizational digital transformation initiatives and long-term data strategy
• Keep abreast of global best practices in MEL systems, data engineering, and digital health

• MEL systems design and management
• Digital health systems development
• Data engineering
• Database design and management
• Data architecture and infrastructure development
• Data integration and interoperability
• API development
• Data analytics and visualization
• Data quality assurance
• Data governance
• Cybersecurity measures
• Capacity building and technical support
• Troubleshooting system issues
• Innovation in data systems
• Digital transformation
• Communication skills
• Problem-solving skills

• Additional training or certification in digital health, health information system, enterprise system or data system is an added advantage
• Minimum of 5–8 years of progressive experience in MEL systems, database design, digital health systems, or data engineering within the development or health sector
• Demonstrated experience designing and implementing end-to-end data systems and architectures
• Experience working with multi-donor programmes and complex data environments especially in Sexual and Reproductive Health is highly desirable
• Proven ability to translate technical concepts into practical solutions for non-technical users