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.
Responsibilities include overseeing daily operations, managing project timelines, and coordinating team activities to ensure efficient workflow. Additionally, the role involves conducting performance evaluations, identifying areas for improvement, and implementing corrective measures when necessary. Collaboration with cross-functional teams is essential to achieve organizational goals, while maintaining strong communication with stakeholders to provide updates and address concerns. Proficiency in project management software and strong leadership skills are required to drive productivity and foster a positive work environment.
MEL Systems Design & Management encompasses the strategic planning, development, and oversight of Measurement, Evaluation, and Learning (MEL) frameworks to ensure robust data collection, analysis, and reporting mechanisms. This role involves collaborating with cross-functional teams to align MEL strategies with organizational goals, designing measurement tools and methodologies, and implementing systems that facilitate real-time data tracking and evaluation. Additionally, responsibilities include managing data quality assurance, overseeing performance metrics, and generating actionable insights to inform decision-making and program improvements. The position requires expertise in MEL frameworks, proficiency in data analysis tools, and strong project management skills to drive continuous learning and adaptive management within the organization.
Lead the strategic design, development, and ongoing enhancement of digital Monitoring, Evaluation, and Learning (MEL) systems for a diverse range of programs and research initiatives. Oversee the full lifecycle of these systems, ensuring they align with program objectives and deliver actionable insights to inform decision-making and program improvements. Foster collaboration among cross-functional teams to integrate MEL frameworks that enhance data-driven strategies and accountability throughout the organization.
Convert program and research requirements into practical system specifications and accessible data solutions.
Oversee the configuration and deployment of digital data collection tools, including mobile-based platforms and electronic registries.
Ensure systems are designed to scale efficiently and adapt seamlessly to meet the changing requirements of the program.
Design and develop robust data architecture frameworks and infrastructure solutions to ensure scalable, reliable, and efficient data management across the organization. Collaborate with cross-functional teams to establish data governance policies, integrate disparate systems, and optimize data workflows for performance and security. Lead initiatives to modernize legacy systems, implement cloud-based architectures, and leverage advanced technologies such as big data platforms, ETL processes, and real-time analytics pipelines. Ensure alignment with business objectives while maintaining compliance with data privacy regulations and industry standards. Provide technical leadership, mentorship to junior engineers, and continuous improvement of data infrastructure to support evolving organizational needs.
Develop and sustain a cohesive data architecture framework that seamlessly integrates various data sources—such as program, research, and administrative systems—to ensure unified accessibility and functionality.
Design and oversee centralized databases and data warehouses to enable streamlined data storage, efficient retrieval, and robust analytical capabilities.
Design and implement robust data pipelines and workflows to streamline and automate data ingestion, ensuring efficient processing, rigorous cleaning, meticulous validation, and timely reporting.
Maintain high standards of system performance, reliability, and thorough documentation of data structures and processes.
Facilitates seamless data integration and interoperability across systems to ensure smooth information exchange and operational efficiency. Develops and maintains interfaces, APIs, and data mapping processes that enable different software applications and databases to communicate effectively. Collaborates with stakeholders to identify integration requirements, resolve interoperability challenges, and optimize data workflows. Implements robust data governance practices to uphold accuracy, consistency, and security throughout integration projects. Monitors system performance, troubleshoots integration issues, and recommends enhancements to improve reliability and scalability. Ensures compliance with industry standards and organizational policies to maintain high levels of data integrity and accessibility.
Ensure seamless integration and functional compatibility across diverse platforms and systems, including MEL tools, national health information systems, and research databases.
Design and deploy APIs as well as integration protocols wherever necessary.
Facilitate adherence to national and international digital health standards and frameworks.
Streamline data sharing processes between internal departments and external partners to ensure efficient and uninterrupted communication.
Data analytics, visualization, and application form the core of this role, requiring proficiency in transforming raw data into actionable insights through advanced analytical techniques and tools. The ideal candidate must possess strong technical skills in data querying, statistical analysis, and the ability to design compelling visual representations to facilitate clear communication of findings. Responsibilities include collecting, processing, and analyzing large datasets to identify trends, patterns, and anomalies, as well as developing interactive dashboards and reports to support decision-making across various departments. Additionally, the position demands expertise in data modeling, predictive analytics, and the use of visualization software such as Tableau, Power BI, or similar platforms to enhance data-driven strategies.
Develop interactive dashboards, data visualization tools, and automated reporting systems for both internal and external stakeholders, overseeing their design and implementation.
Provide advanced analytics support by maintaining structured, accessible data essential for accurate statistical analysis and robust modelling efforts.
Work in close partnership with the Statistician/Epidemiologist to facilitate rigorous, high-quality data analysis.
Foster a data-driven culture by guaranteeing that systems produce clear, practical insights that are easily accessible to users.
Data quality, security, and governance are critical components of our operations, ensuring that information is accurate, protected, and managed in compliance with regulatory standards. This role requires a strong understanding of data integrity principles, robust security protocols, and effective governance frameworks. Key responsibilities include maintaining high data standards, implementing security measures to safeguard sensitive information, and overseeing compliance with organizational policies and external regulations. Candidates must demonstrate expertise in data management, risk assessment, and adherence to industry best practices.
Establish robust data quality assurance frameworks, incorporating validation rules, periodic audits, and systematic data cleansing procedures to ensure accuracy and reliability.
Create, introduce, and enforce structured data governance frameworks that establish clear data standards, define stringent access controls, and manage user permissions effectively.
Verify adherence to data protection regulations, ethical guidelines, and internal policies to maintain organizational integrity and regulatory compliance.
Enhance data backup protocols, recovery systems, and cybersecurity frameworks to ensure robust protection and resilience against potential threats.
We provide capacity building initiatives and technical support services to enhance organizational effectiveness and foster sustainable development. Our role involves designing tailored training programs, offering expert guidance, and assisting partners in implementing best practices. Additionally, we facilitate knowledge-sharing sessions and develop customized tools to strengthen institutional capabilities. Strong collaboration and communication skills are essential, along with a proven track record in delivering impactful capacity-building interventions. Familiarity with monitoring and evaluation frameworks is highly desirable.
Offer continuous technical assistance to program and research teams in the effective utilization of Monitoring, Evaluation, and Learning (MEL) systems and digital tools.
Create comprehensive user guides, establish detailed standard operating procedures (SOPs), and design engaging training materials.
Facilitate training programs designed to strengthen staff proficiency in data collection, management, and utilization.
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 implementation and integration of digital health innovations and cutting-edge technologies, such as cloud-based platforms, mobile data systems, and AI-driven analytics, where applicable.
Assist in driving the organization’s digital transformation efforts and the development of its long-term data strategy.
To stay informed about cutting-edge methodologies in Monitoring, Evaluation, and Learning (MEL) systems, data engineering, and digital health, actively follow emerging trends and advancements in these fields.
Personal Attributes
Proficiency in digital health, health information systems, enterprise systems, or data systems, along with relevant training or certifications, would be considered an asset.
With a minimum of five to eight years of relevant experience, candidates should demonstrate a progressive background in Monitoring, Evaluation, and Learning (MEL) systems, database design, digital health systems, or data engineering—particularly within development or healthcare sectors.
Proven expertise in designing and deploying comprehensive end-to-end data systems and architectures is required. Candidates must possess a track record of successfully implementing such frameworks in previous roles.
Proficiency in multi-donor program management and navigating intricate data ecosystems—particularly within Sexual and Reproductive Health—is strongly preferred.
Demonstrated skill in converting complex technical information into accessible solutions tailored for audiences without a technical background.
Qualifications
BA/BSc/HND
Experience Required
5 - 8 years
