Improved monitoring through IPTT, total reach, FRM, QB, and activity-tracking visuals.
Designed data schema and built ETL pipelines using Python.
- App Developer
- Data Visualizer
- Database Developer
Hi, I'm Eklemis Santo Ndun, a Data & Digital Systems professional with over seven years of experience helping education, health, and child protection programs become more data-driven.
Hi, I’m Eklemis Santo Ndun, a Data & Digital Systems professional with over seven years of experience helping education, health, and child protection programs become more data-driven. I enjoy turning messy field data into reliable dashboards, automated processes, and user-friendly tools that empower teams to make evidence-based decisions.
I thrive in cross-functional settings, designing end-to-end data pipelines using Python and SQL, building secure databases, and delivering impactful digital solutions—from Power BI dashboards to internal apps that streamline monitoring and reporting.
Improved monitoring through IPTT, total reach, FRM, QB, and activity-tracking visuals.
Designed data schema and built ETL pipelines using Python.
Manage end-to-end monitoring workflows, field data collection, validation, cleaning, integration, and reporting; maintain secure sponsorship and program databases with data accuracy, standards, and routine backups; develop dashboards (Power BI, Looker Studio) to visualize indicators and support decision-making; build internal apps to automate processes and speed up M&E; lead Python- and SQL-based data transformation pipelines to produce clean, analysis-ready datasets; coordinate AFU/Enrollment cycles ensuring completeness and timely submissions; train staff on digital tools and data quality practices.
Manage end-to-end monitoring workflows, field data collection, validation, cleaning, integration, and reporting. Maintain secure sponsorship and program databases with data accuracy, standards, and routine backups. Develop dashboards (Power BI, Looker Studio) to visualize indicators and support decision-making. Build internal apps to automate processes and speed up M&E workflows. Lead data transformation pipelines using Python and SQL to produce clean, analysis-ready datasets. Coordinate AFU/Enrollment cycles ensuring completeness, photo quality, and timely submissions. Train staff on digital tools, monitoring workflows, and data quality practices.
Managed Sponsorship data systems, ensured accuracy, security, and compliance across program sectors; maintained ASISt database reliability through structured backups, data protection protocols, and disaster recovery; validated enrollment and AFU data, trained data collectors, and ensured consistent data quality across communities; collaborated with Global Sponsorship Operations to resolve data issues and improve workflows; developed internal tools that automated validation, improved data entry accuracy, and reduced operational workload; built dashboards for real-time monitoring of Sponsorship activities and program progress.
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