Fundi James

Data Analytics professional and Data Analytics Executive (Business Intelligence & Data Engineering) with expertise in designing ETL pipelines, analytics-ready datasets, and enterprise reporting solutions for international development and humanitarian programmes. Experienced in SQL, Python, Power BI, PostgreSQL, AWS data warehousing, and dashboard automation, with a strong track record of analysis of health, nutrition, epidemiological, survey, and humanitarian datasets across Africa.

Data Analytics Executive (Business Intelligence and Data Engineering-End-to-End BI Systems Owner) - Dalberg Research

(2024-01)

• Data Ingestion, ETL/ELT Pipelines and Data Quality Management: Designed and maintained analytics-ready datasets, reusable analytical models, and curated reporting layers that supported enterprise dashboards and self-service analytics.
• Data Transformation, Statistical Modeling and Data Processing Layer: Performed advanced data analysis using Python, R, Stata, SPSS, and Excel. Designed and maintained relational and dimensional data models to support Power BI reporting and KPI dashboards. Supported scalable data storage and processing using AWS data warehouse for high-volume analytical workloads.
• BI analytics and Reporting Layer, KPI and Dashboard Development: Developed 15+ executive dashboards supporting 20+ projects across East and West Africa, reducing manual reporting time by 40%. Produced technical documentation, metadata, integration documentation, ETL/ELT process documentation, dashboard user guides and data dictionaries. Built curated analytics layers that supported reusable reporting, KPI monitoring, and downstream analytical applications.
• Data Engineering, Version Control and Automation: Designed and implemented Python-based ETL/ELT reproducible pipelines for automated BI reporting workflows, reducing manual reporting effort and ensuring consistent, production-ready data delivery for dashboards and KPI systems. Used GitHub for version control and collaborative development of BI scripts, supporting structured deployment of reproducible analytics workflows and reporting systems.
• Data Lifecycle: Managed complete data life-cycle including ingestion, validation, transformation, storage, visualization and reporting.
• Data governance: Developed automated data validation and quality assurance procedures to ensure completeness, consistency, and integrity of analytical datasets.
• BI Insights, Monitoring and Decision Support Layer: Applied advanced analytics and AI-enhanced monitoring and evaluation approaches to generate actionable insights from complex datasets. Translated analytical outputs into decision-support insights, program frameworks, and performance monitoring systems for stakeholders across development and research programs.
• Change Management and BI System Improvement: Supported change management initiatives during deployment of Business Intelligence solutions by collaborating with business users, documenting processes and improving reporting workflows.
• Capacity Development: Trained and supported project teams and stakeholders on BI dashboards, data quality standards, reporting workflows, and data-driven decision-making, improving adoption of Business Intelligence solutions.

Data Analyst - datamax analytics

(2023-01 - 2024-12)

• Data Collection and Requirements Gathering: Translated business requirements into scalable analytical datasets, ETL/ELT workflows, KPI definitions, and BI dashboards.
• Data Analysis: Conducted data-driven analysis and interpretation of structured datasets to identify trends, patterns, and insights supporting evidence-based decision-making and operational planning.
• Data Visualization: Developed interactive dashboards and data visualization products using Tableau and Power BI to communicate key performance indicators (KPIs), monitoring results, and decision-support insights to stakeholders.
• Data Quality Assurance: Performed data cleaning, preprocessing, and quality assurance checks to ensure accuracy, reliability, and integrity of datasets used for downstream analytics and reporting.
• Manage online surveys and databases: Managed digital survey systems and data collection pipelines using REDCap, ensuring high-quality data capture for quantitative and qualitative research and assessment activities.
• Collaborative Decision-Making: Supported cross-functional collaboration and stakeholder engagement, translating complex analytical outputs into actionable insights for program and operational decision-making.
• Reporting: Contributed to analytical reporting and monitoring frameworks used for tracking performance indicators, supporting program evaluation, targeting decisions, and resource allocation analysis.

Content Supervisor-2019 Population and Housing Census - Kenya National Bureau of Statistics

(2019-01 - 2019-12)

• Data Collection Supervision: Supervised the data collection process, ensuring accuracy and adherence to protocols.
• ICT Integration: Utilized ICT infrastructure for secure data collection, encryption, and transmission to central servers.

Research Internship - Kenya Agricultural and Livestock Research Organization (KALRO)

(2013-01 - 2013-12)

• Data Management: Performed accurate data entry, collection, and analysis to support data-driven insights.
• Model Development: Developed data models and machine learning algorithms for predictive analysis and decision-making.
• Report Generation: Created comprehensive reports to communicate key findings and trends effectively.

Master of Science - Applied Statistics - Jomo Kenyatta University of Agriculture and Technology (JKUAT) (2021-01 - 2023-12)

Bachelor of Science - Applied Statistics with Computing - Karatina University (2009-01 - 2014-12)