About the role

The Data Analyst is responsible for transforming raw health data into actionable insights that guide program strategy and operational decision-making at T4Health and among our partner organisations. This role involves managing end-to-end data processes, from acquisition and preparation to analysis, visualisation and dissemination.

What you'll do

• Contribute to the development and maintenance of standard reporting frameworks, indicator dictionaries, metadata catalogues, and data standards.
• Monitor data quality, identify inconsistencies, anomalies, and outliers, and implement corrective measures to improve data accuracy and reliability.
• Ensure compliance with the Kenya Data Protection Act (2019) and other applicable data privacy, security, and governance requirements.
• Support the development, implementation, and enforcement of enterprise data governance policies, standards, and best practices.
• Review and validate how key indicators and KPIs are calculated across source systems (e.g., DHIS2, EMRs, and programme databases) compared to the enterprise data lake.
• Identify, document, and justify discrepancies between source-level and data lake-level KPI calculations, collaborating with Data Engineering teams to resolve inconsistencies.
• Ensure analytical scripts, reports, dashboards, and documentation are accurate, accessible, reproducible, and maintained in accordance with organizational standards.
• Conduct exploratory, diagnostic, and trend analyses to support programme monitoring, evaluation, and evidence-based decision-making.
• Identify recurring analytical requirements and develop reusable products, parameterized scripts, templates, and reporting solutions to improve efficiency.
• Interpret analytical outputs and provide clear, actionable recommendations to project teams, business stakeholders, and leadership.
• Collaborate with Data Scientists to research, engineer, and validate features, derived variables, and data transformations for analytical models.
• Design, develop, and maintain dynamic self-service dashboards and reporting solutions using platforms such as Microsoft Power BI, Tableau, or equivalent Business Intelligence tools.
• Develop dashboards and reports as reusable products with standardized documentation, configurable parameters, filters, and automated refresh logic.
• Generate periodic, ad hoc, and executive-level analytical reports, dashboards, visualizations, and performance summaries.
• Collaborate with internal teams, government agencies, and external stakeholders to understand evolving business and reporting requirements.
• Work closely with Data Engineering teams to communicate analytical requirements and continuously improve data models, pipelines, and data lake structures.
• Provide user training, mentorship, and ongoing support on data tools, dashboards, analytics products, and self-service reporting capabilities.

What we're looking for

• Bachelor's degree in Data Science, Statistics, Computer Science, Medical Epidemiology, Health Informatics, Mathematics, or a related field.
• Minimum of 3–5 years of hands-on experience in data analytics, business intelligence, analytics engineering, or a related field, preferably within healthcare, public health, or development programmes.
• Demonstrated experience designing and developing interactive dashboards and reports using Microsoft Power BI, Tableau, or similar Business Intelligence platforms.
• Strong ability to analyze and interpret complex datasets, generate actionable insights, and present findings to both technical and non-technical audiences.
• Proficiency in SQL for data extraction, transformation, analysis, and performance optimization.
• Hands-on experience with programming languages such as Python, R, or equivalent analytical tools for data analysis and visualization.
• Strong understanding of data modeling, data quality, and data governance principles.
• Experience working with relational databases, data warehouses, and large-scale datasets.
• Excellent analytical, critical thinking, and problem-solving skills.
• Strong written and verbal communication skills with the ability to communicate insights effectively to stakeholders.
• Experience collaborating with cross-functional teams including Data Engineering, Product, Programme, and Business teams.
• Ability to manage multiple priorities while delivering high-quality analytical outputs in a fast-paced environment.

Nice to have

• Exposure to health information systems such as DHIS2, Electronic Medical Records (EMRs), or Health Information Exchanges (HIE) is an added advantage.
• Experience working with cloud-based data platforms such as Microsoft Azure, AWS, or Google Cloud Platform (GCP).
• Familiarity with data visualization best practices, data storytelling, and dashboard design principles.
• Experience using version control and collaborative development tools such as Git or Azure DevOps.

• Contribute to the development and maintenance of standard reporting frameworks, indicator dictionaries, metadata catalogues, and data standards.
• Monitor data quality, identify inconsistencies, anomalies, and outliers, and implement corrective measures to improve data accuracy and reliability.
• Ensure compliance with the Kenya Data Protection Act (2019) and other applicable data privacy, security, and governance requirements.
• Support the development, implementation, and enforcement of enterprise data governance policies, standards, and best practices.
• Review and validate how key indicators and KPIs are calculated across source systems (e.g., DHIS2, EMRs, and programme databases) compared to the enterprise data lake.
• Identify, document, and justify discrepancies between source-level and data lake-level KPI calculations, collaborating with Data Engineering teams to resolve inconsistencies.
• Ensure analytical scripts, reports, dashboards, and documentation are accurate, accessible, reproducible, and maintained in accordance with organizational standards.
• Conduct exploratory, diagnostic, and trend analyses to support programme monitoring, evaluation, and evidence-based decision-making.
• Identify recurring analytical requirements and develop reusable products, parameterized scripts, templates, and reporting solutions to improve efficiency.
• Interpret analytical outputs and provide clear, actionable recommendations to project teams, business stakeholders, and leadership.
• Collaborate with Data Scientists to research, engineer, and validate features, derived variables, and data transformations for analytical models.
• Design, develop, and maintain dynamic self-service dashboards and reporting solutions using platforms such as Microsoft Power BI, Tableau, or equivalent Business Intelligence tools.
• Develop dashboards and reports as reusable products with standardized documentation, configurable parameters, filters, and automated refresh logic.
• Generate periodic, ad hoc, and executive-level analytical reports, dashboards, visualizations, and performance summaries.
• Collaborate with internal teams, government agencies, and external stakeholders to understand evolving business and reporting requirements.
• Work closely with Data Engineering teams to communicate analytical requirements and continuously improve data models, pipelines, and data lake structures.
• Provide user training, mentorship, and ongoing support on data tools, dashboards, analytics products, and self-service reporting capabilities.

• SQL
• Python
• R
• Power BI
• Tableau
• Big-data analytics
• Business Intelligence
• Data Visualization
• Data Governance
• Exploratory Data Analysis

• Bachelor's degree in Data Science, Statistics, Computer Science, Medical Epidemiology, Health Informatics, Mathematics, or a related field.
• Minimum of 3–5 years of hands-on experience in data analytics, business intelligence, analytics engineering, or a related field, preferably within healthcare, public health, or development programmes.
• Demonstrated experience designing and developing interactive dashboards and reports using Microsoft Power BI, Tableau, or similar Business Intelligence platforms.
• Strong ability to analyze and interpret complex datasets, generate actionable insights, and present findings to both technical and non-technical audiences.
• Proficiency in SQL for data extraction, transformation, analysis, and performance optimization.
• Hands-on experience with programming languages such as Python, R, or equivalent analytical tools for data analysis and visualization.
• Strong understanding of data modeling, data quality, and data governance principles.
• Experience working with relational databases, data warehouses, and large-scale datasets.
• Excellent analytical, critical thinking, and problem-solving skills.
• Strong written and verbal communication skills with the ability to communicate insights effectively to stakeholders.
• Experience collaborating with cross-functional teams including Data Engineering, Product, Programme, and Business teams.
• Ability to manage multiple priorities while delivering high-quality analytical outputs in a fast-paced environment.
• Exposure to health information systems such as DHIS2, Electronic Medical Records (EMRs), or Health Information Exchanges (HIE) is an added advantage.
• Experience working with cloud-based data platforms such as Microsoft Azure, AWS, or Google Cloud Platform (GCP).
• Familiarity with data visualization best practices, data storytelling, and dashboard design principles.
• Experience using version control and collaborative development tools such as Git or Azure DevOps.