Monitoring & Evaluation Officer - Data Quality and Analytics

Monitoring & Evaluation Officer - Data Quality and Analytics

Mbabane, Eswatini

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Monitoring & Evaluation Officer - Data Quality and Analytics

About Palladium Palladium is a global impact company that works with governments, communities, businesses, and partners to strengthen systems and deliver sustainable development outcomes. In Eswatini, the position supports health information, monitoring, data quality, analytics, and data-use priorities implemented through Data.

FI / Project Nexus in collaboration with the Ministry of Health and other stakeholders.

This Opportunity Palladium is seeking a Monitoring & Evaluation Officer - Data Quality and Analytics to support implementation of the Eswatini monitoring, evaluation, and strategic information portfolio. The role strengthens the availability, quality, analysis, interpretation, and use of routine health information, with particular emphasis on CMIS and related national information systems, National/G2G Memorandum of Understanding (MoU) indicators, routine data quality assurance, dashboards and analytics, facility and regional data reviews, and data-driven Quality Improvement Projects (QIPs).

The Officer works closely with the M&E Manager, Ministry of Health structures, regional and facility teams, data engineering, and digital health colleagues to translate routine data into credible reporting, actionable performance insights, and documented improvement. The role also supports milestone verification, evidence management, audit readiness, and institutionalization of sustainable M&E practices.

Primary Responsibilities

1. M&E systems strengthening, planning and milestone verification

• Support development, review and operationalization of project M&E/MEL frameworks, indicator registers, performance monitoring plans, workplans, reporting tools and milestone verification approaches.
• Develop and maintain practical monitoring tools, gap-analysis tools, work breakdown structures, Means of Verification matrices, evidence trackers and action trackers linking planned activities to measurable outputs and results.
• Support routine review of milestone progress, completeness and quality of verification evidence, and preparation of evidence packages for internal, MoH and donor review.
• Support the maintenance of organized, traceable, and audit-ready documentation for reported results, including source records, validation outputs, approvals, review notes, and follow-up actions.

2. Data quality assurance, validation, and CMIS data integrity

• Plan, coordinate and support routine data quality assessments, data validation exercises, and internal verification of CMIS and other priority health information system data.
• Assess data completeness, timeliness, consistency, accuracy, concordance and reporting availability, and document findings by indicator, program, facility, and data source.
• Maintain DQA findings and corrective-action trackers, monitor closure of identified gaps, and work with regional, facility, program, and technical teams on remediation.
• Support validation of deduplication processes and other data-quality controls for CMIS, including review of duplicate Patient ID issues, matching outputs, concordance results, and documentation of approved corrective processes.
• Support review, validation and harmonization of data-generation and aggregation scripts, identify data-quality issues affecting outputs, and collaborate with data engineering/development teams on optimization, version control, and documentation.

3. National/G2G MoU indicator monitoring and reporting

• Lead the coordination of mapping and validation of priority National/G2G MoU indicators, including indicator definitions, reporting requirements, data elements, approved sources, frequency, and data ownership.
• Support baseline and data-coverage assessments to determine indicator availability, reporting readiness and gaps across CMIS, NDR, DHIS2 and other relevant national/program systems.
• Prepare and maintain indicator mapping matrices, coverage summaries, and analytical outputs to inform reporting readiness, facility/program prioritization, and CMIS scale-up decisions.
• Coordinate extraction, validation, quality assurance, consolidation, and documentation of MoU indicator results for routine and quarterly reporting.
• Work with M&E, data engineering, and MoH teams to validate results available through NDR pipelines and dashboards and ensure discrepancies are documented, investigated, and resolved.

4. Analytics, dashboards, and data integration

• Conduct descriptive, trend, variance, comparative and facility/program-level analyses of routine health data to identify performance patterns, reporting gaps and emerging priorities.
• Support the development, validation and maintenance of dashboards, visualizations, and routine analytical products for agreed program areas, including monitoring of MoU-aligned indicators.
• Support indicator and data-element mapping for CMIS, DHIS2, NDR and other national platforms, including validation of aggregated outputs and migration/exchange results where applicable.
• Conduct data and dashboard quality checks, reconcile outputs to approved source data and document exceptions before information is used for reporting or decision-making.

5. Routine data reviews and regional/RHMT support

• Coordinate and technically support MOH routine facility, regional and national data-review, and Data-for-Action processes, including preparation of validated datasets, dashboards, performance summaries, and discussion materials.
• Support RHMTs and other regional structures to review workplans, implementation status, performance data, Means of
• Verification and outstanding actions, and to develop practical action plans.
• Maintain data-review calendars, attendance/evidence records, meeting summaries, and action trackers, and follow up implementation or escalation of agreed priority actions.
• Promote routine use of validated CMIS, DHIS2, NDR and other relevant data for planning, program monitoring, service improvement, and management decisions.
• Provide targeted mentorship and capacity strengthening to MoH, regional and facility teams in data interpretation, data-quality review, dashboard use and evidence-based decision-making.

6. Quality Improvement Projects (QIPs)

• Use routine performance data, DQA findings and data-review outputs to support identification and prioritization of national, program, regional and facility QIPs.
• Support development of QIP problem statements, indicators, baselines, targets, measurement plans, and monitoring tools, ensuring improvement is measurable using credible routine data.
• Monitor QIP implementation and performance over time; analyze results against baseline and targets; identify implementation or data-quality barriers; and support course correction.
• Support QI initiatives involving clinical/program workflows and digital systems, including data documentation, CMIS/LIS integration, screening, dispensing, and continuity-of-care processes where these fall within approved workplans.
• Strengthen QIP documentation through standardized journals/reports, performance summaries, learning products, and incorporation of QIP results into routine review platforms.

7. National reporting

• Assist MoH to develop, standardize and disseminate information products such as factsheets, QSCRs, annual/quarterly reports, dashboards, and analytical briefs.
• Assist MoH to develop and apply standardized reporting templates, indicator definitions, data-management guidance, and SOPs to improve consistency, reproducibility, and reporting quality.

8. CMIS implementation, monitoring, and capacity strengthening

• Support monitoring and verification of CMIS inpatient implementation, including readiness, training, UAT, go-live, active use, reporting and post-implementation stabilization evidence.
• Support inpatient and other CMIS capacity-strengthening activities with MoH/HMIS, regional and facility teams, focusing on correct workflows, data integrity, reporting, and dashboard use.
• Analyze implementation and post-go-live issues affecting data quality or use, including workflow, data integrity, connectivity/reporting dependencies, and dashboard/report outputs, and ensure issues are documented and followed through appropriate action channels.
• Support routine monitoring of CMIS reliability and reporting performance where M&E verification or analytical input is required.

9. Collaboration, learning, and adaptive management

• Work collaboratively with the M&E Manager, Data Use Analysts, Data Engineer, digital health/CMIS teams, regional teams, MoH counterparts and other stakeholders to deliver integrated monitoring and data-use support.
• Contribute to bi-weekly, monthly, and other routine technical/performance updates, clearly documenting achievements, challenges, decisions, next steps, an