Monitoring, Evaluation, Research and Learning Data Manager

About the role

The Monitoring, Evaluation, Research and Learning (MERL) Data Manager will lead the design, implementation and continuous improvement of MERL systems for the Food & Agriculture Pillar. The role ensures that data are collected, managed, analysed, visualised and reported efficiently to provide high‑quality evidence for programme implementation, adaptive management and donor accountability.

Key responsibilities

• Design, implement and refine MERL systems for the Food & Agriculture Pillar.
• Develop and administer digital data collection tools and programme databases, including the DMIS platform.
• Coordinate data collection, validation, cleaning, integration, storage, analysis, visualisation and reporting.
• Create and maintain interactive dashboards, automated reports and business‑intelligence solutions for real‑time performance insights.
• Provide technical support for baseline, midline, endline, outcome and impact assessments, including statistical analysis and dissemination of findings.
• Document and share data best practices, innovations and knowledge products.
• Build capacity of programme teams and implementing partners in MERL methodologies, digital data systems and business‑intelligence tools.
• Collaborate with internal and external stakeholders to strengthen digital MERL systems and support programme design, implementation and evaluation.
• Support development and maintenance of GIS‑enabled datasets, maps and spatial analyses.

Required profile

• Proven experience in monitoring, evaluation, research and learning (MERL) for development programmes.
• Strong background in data management, statistical analysis and evidence generation.
• Experience working with implementing partners, donors and multi‑disciplinary teams.

Required skills

• DMIS platform administration
• Geographic Information Systems (GIS)
• Data visualisation and dashboard creation
• Business intelligence tools (e.g., Power BI, Tableau)
• Statistical analysis (e.g., SPSS, R, Stata)