Position Title: Sr. Meal Expert
Employer: Welthungerhilfe (WHH) - Ethiopia
Employment: Full-Time | Contract
Place of Work: Addis Ababa - Ethiopia
Posted date: 1 hour ago
Deadline: March, 27/2026 (14 days left)
in Addis Abeba
The position is to be filled as soon as possible, with an initial contract duration of one year. There are very good prospects for an extension. Employment location will be Addis Ababa, Ethiopia .
To support evidence-based programming by building practical data systems, ensuring high-quality and responsible data management, and translating programme data into clear insights that improve decision-making and programme outcomes.
Your responsibilities
- A standardised country data model for key programmes (indicator library, disaggregation, definitions, codebooks).
- Dashboards and monthly/quarterly decision products used by programme and management teams.
- Routine automated data quality checks (completeness, consistency, outliers, duplicates) implemented and documented.
- A digital data collection approach (forms, training, field workflows) that reduces errors and speeds up reporting.
- A feedback/CFM dataset and trend analysis approach that supports accountability and learning (privacy-safe).
- A simple GDPR-aligned data governance package (SOPs, templates, retention rules, access controls) adopted by projects and partners.
- Support the development and harmonisation of project-specific MEAL plans, indicator tracking tools, reporting templates, and monitoring schedules in collaboration with programme teams and partners.
- Design and maintain a MEAL data architecture for programme monitoring (indicator library, codebooks, metadata, and version control).
- Set up and maintain a secure programme database/structured repository for MEAL datasets, tools, and documentation (including access control and naming conventions).
- Develop and enforce data governance procedures: lawful basis/consent language, data minimisation, retention schedules, secure storage, and safe sharing rules.
- Create SOPs for the full data cycle: collection, cleaning, validation, storage, analysis, publication, and archiving/deletion.
- Support partner data systems alignment (minimum standards, tool templates, and light-touch audits).
- Analyse monitoring data and provide actionable recommendations to programme teams and management to support adaptive project management and evidence-based decision-making.
- Contribute to donor and internal reporting through verification and analysis of indicator progress and supporting documentation.
- Translate logframes/ToCs into analytical questions and build analysis plans aligned to decision points (e.g., targeting, seasonality, pipeline planning).
- Develop and maintain dashboards and analysis packs (Power BI/Tableau/Excel) for programme performance, outcome trends, and quality flags.
- Implement automated data checks (outlier rules, duplicate detection, missing disaggregation flags) and document the logic for maintainability.
- Run deeper analyses when needed: pre/post comparisons, cohort tracking, basic forecasting or risk signals (only where data quality supports it).
- Support proposal design and reporting with indicator logic, disaggregation plans, and data evidence (baseline values, assumptions, benchmarks).
- Support the development and maintenance of project monitoring databases including digital beneficiary master lists and distribution tracking systems where applicable.
- Lead the design and QA of digital data collection tools (CommCare), including skip logic, constraints, and translations.
- Embed privacy-by-design into tools (minimum necessary fields, role-based access, secure device/data handling).
- Train enumerators and programme teams on digital workflows, field protocols, informed consent, and common error prevention.
- Create rapid feedback loops from field data: daily/weekly checks, issue logs, and corrective actions.
- Maintain a library of reusable forms, question banks, and standard disaggregation fields to improve consistency across projects.
- Support the implementation and monitoring of WHH accountability standards, including Feedback and Complaints Response Mechanisms (FCRM), and ensure alignment with safeguarding and Code of Conduct requirements.
- Strengthen complaints and feedback mechanisms (CFM): data capture, categorisation, referral workflows, and closing-the-loop tracking.
- Ensure safe handling of sensitive feedback (including safeguarding-related cases) with clear confidentiality rules, access restrictions, and referral pathways.
- Analyse feedback trends (themes, volumes, resolution times, sensitive categories) and produce actionable insights for programme adaptation.
- Where appropriate and safe, apply basic text analytics to feedback comments (topic tagging/trend detection) with strict privacy controls and human review.
- Monitor and support the implementation of evaluation recommendations and ensure lessons learned are integrated into programme improvement and future project design.
- Develop a learning agenda and help teams plan evaluations and studies that answer priority questions (relevance, effectiveness, inclusion, accountability).
- Ensure baselines, endlines, and evaluations follow appropriate methods and produce usable recommendations.
- Produce short evidence products: learning briefs, decision notes, and ‘what changed’ summaries combining quantitative and qualitative data.
- Facilitate after-action reviews and learning workshops, and support action tracking.
- Act as the country office focal point for programme data protection and GDPR-aligned practices in coordination with management and relevant support functions.
- Maintain practical data protection documentation for MEAL (data inventories for key datasets, access lists, retention/deletion schedules, and incident/issue logs as applicable).
- Support data processing agreements and partner due diligence inputs for programme data systems (as required), and advise teams on minimum safeguards.
- Provide guidance on safe data sharing for donor reporting, evaluations, and learning products (anonymisation/pseudonymisation where needed).
- Support staff capacity building on data protection, confidentiality, and responsible data use across projects and partners.
- Assess MEAL capacity gaps among partners and programme teams and support the development and implementation of MEAL capacity strengthening plans.
- Facilitate reflection meetings, learning sessions, and cross-project knowledge sharing within the Country Office and with implementing partners.
- Coach MEAL and programme staff (and key partners) on data literacy: interpreting indicators, reading dashboards, and asking good questions of data.
- Build practical skills on data quality, sampling basics, digital tools, and analysis workflows.
- Promote a culture of data use through regular review meetings and simple ‘data-to-action’ routines.
- AI may be used as a support tool for analytics (e.g., pattern detection, text tagging, drafting narrative summaries) only when:
- Sensitive data is protected and processing complies with WHH data protection and safeguarding requirements.
- Outputs are checked by humans before any decision, reporting, or external sharing (human-in-the-loop).
- Methods are documented and explainable (what data, what rules/model, what limitations).
- AI is not used to make eligibility/assistance decisions without approved governance and clear safeguards.
Qualification
- Experience working in INGO or development programmes with strong understanding of project cycle management and donor compliance requirements.
- Experience facilitating trainings, workshops, and capacity development activities for programme staff and partners.
- Education: Degree in statistics, data science, economics, social sciences, public health, or related field (or equivalent experience).
- Experience: 5+ years in MEAL, research, programme quality, information management, or analytics.
- Strong understanding of MEAL frameworks: logframes/ToC, indicators, DQAs, evaluation basics, and learning processes.
- Demonstrated experience producing analytical products that influenced programme decisions (dashboards, analysis packs, decision briefs).
- Digital data collection experience (Kobo/ODK/CommCare or similar) including form QA and field workflows.
- Data analysis skills: advanced Excel (Power Query preferred) and at least one of Power BI / Tableau.
- Solid understanding of responsible data management (confidentiality, informed consent, data minimisation, retention, safe sharing).
- Ability to explain analysis clearly to non-technical colleagues and build their confidence in using data.
- Excellent spoken and written English and Amharic
Our offer
We offer you the opportunity to work in a responsible and interesting field as part of an extremely dedicated team. Welthungerhilfe attaches great importance to the personal and professional development of its employees. Remuneration is based on our gender-independent salary scale.
Please send your application via our online recruiting system by March 27, 2026. Welthungerhilfe is committed to fighting terrorism in all its activities. Accordingly, any applicant who is offered employment will be screened against lists of known and suspected terrorists.
