Description

Irembo

is a technology company that designs and develops digital products to ease the accessibility of services in users’ everyday lives worldwide, starting with Rwanda. Our pioneer products, IremboGov and IremboPay, have enabled Rwandan citizens and foreigners to access and pay for over 150 public services online through our one-stop-shop e-governance and payment platforms. To date, we have facilitated over 30 million transactions through our platforms and have ambitious goals to scale our technology worldwide to enable more governments and institutions to serve their citizens better. More information is available on irembo.com.;Our flagship platforms, IremboGov and IremboPay, have transformed how government services are accessed and paid for, proving our ability to simplify complex processes and enhance public engagement.;We are now bringing the same innovation to healthcare to ensure every Rwandan has access to efficient, high-quality digital health services. Building on the legacy of Babyl Rwanda, which introduced telemedicine in 2016 and delivered over 3.5 million consultations in seven years through USSD and voice calls, and was integrated with health facilities for diagnostics, prescriptions, and referrals.;Our first step is the launch of a national-scale telemedicine platform, designed to expand access and convenience, enabling services that can only be better delivered via telemedicine, such as remote consultations, chronic disease management, and preventive care follow-ups. It also sets a new paradigm for healthcare delivery by leveraging advanced technologies, including AI, to improve diagnosis, personalize care, and optimize health system efficiency.

Role overview

We are seeking an Analytics Engineer

to build and maintain the analytics data layer that powers reporting, monitoring, product analytics, and evaluation across the TeleClinic platform.;This role sits at the intersection of data engineering and analytics. The Analytics Engineer is responsible for transforming raw data into analytics-ready datasets, optimizing data models and queries, and designing data marts that enable Data Analysts, Product teams, and Monitoring & Evaluation stakeholders to deliver reliable insights.;The role directly supports Product, Engineering, Clinical Governance, Operations, and MEL teams by ensuring analytics data is accurate, performant, well-structured, and fit for business and clinical use cases

Key responsibilities

Key responsibilities are:

• Design, build, and maintain data transformations that convert raw clinical, operational, and platform data into analytics-ready health datasets.
• Optimize transformations and queries to ensure performance, scalability, and reliability while handling high-volume, sensitive healthcare data.
• Apply analytics engineering best practices to ensure transformations are maintainable, auditable, and well-documented.
• Design and maintain analytics data models (fact tables, dimensions, and marts) that accurately represent: Teleconsultations and encounters, Patient journeys and service turnaround times, Referrals, follow-ups, and continuity of care
• Ensure data models align with clinical workflows, service delivery processes, and reporting needs.
• Maintain consistent and reusable structures to support clinical quality monitoring, operations, and evaluation.
• Work closely with Data Analysts and M&E teams to translate clinical, operational, and business requirements into analytics marts.
• Support the implementation of business- and health-related marts used for dashboards, monitoring, product analytics, and evaluation.
• Ensure analysts are enabled with trusted, analytics-ready datasets that support accurate interpretation and decision-making.
• Define, standardize, and maintain core TeleClinic metrics, including consultations, wait times, referrals, follow-ups, and selected quality indicators.
• Implement data quality checks and validations to ensure accuracy, completeness, and consistency of health data.
• Identify and resolve data issues that may impact clinical reporting, service monitoring, or decision-making, in collaboration with Data Engineering and Product teams.
• Collaborate with Data Engineers on ingestion pipelines, schema changes, and performance optimization for health data.
• Partner with Product, Engineering, and Clinical teams to ensure platform and event data accurately reflect healthcare delivery and user interactions.

Qualifications

Main qualifications are:

• Bachelor’s degree in Computer Science, Data Engineering, Data Science, Statistics, Engineering, Health Informatics, or a related field.
• 3+ years of experience in an Analytics Engineer, Data Engineer, or BI Engineering role, with hands-on responsibility for data transformations and analytics data modeling.
• Strong proficiency in SQL and experience working with analytical data warehouses.
• Hands-on experience designing and maintaining data transformations using frameworks such as dbt or equivalent.
• Strong understanding of analytics data modeling (fact tables, dimensions, star schemas, analytics marts).
• Experience optimizing data models and queries for performance, scalability, and reliability.
• Experience working with health, clinical, or service delivery data, with an understanding of data accuracy and reliability requirements in healthcare contexts.
• Ability to collaborate closely with Data Analysts, Product teams, and Engineers to translate business and clinical requirements into analytics-ready data models.
• Strong documentation practices and attention to data quality and consistency, especially for health-related metrics.