M-KOPA is a fast-growing FinTech company offering millions of underbanked customers across Africa access to life-enhancing products and services. From our roots as the pioneer in pay-as-you-go “PayGo’” solar energy for off grid homes, we have grown into one of the most advanced connected asset financing platforms in the world, empowering a broad range of customers to achieve progress in their lives.
We are looking for a Senior Analytics Engineer to join our team at M-KOPA. Build the analytics infrastructure that powers data-driven decisions across our FinTech platform serving millions in Africa.
The Impact - Your data pipelines and models will directly enable product teams to understand and expand financial inclusion for millions across Africa.
We've already helped over 5 million customers access over $1.5 billion in credit. It's your chance to shape how data drives decisions that literally transform lives across an entire continent.
The Opportunity:
Mission-driven analytics: Every dataset you model helps teams measure and expand financial inclusion for under-banked populations
Global recognition: Join a company named by TIME 100 as one of the world's most influential and by the Financial Times as Africa's fastest-growing for 4 consecutive years (2022-2025)
Scale challenges: Build analytics infrastructure processing data for millions across multiple African markets
Environmental impact: We're carbon-negative, having displaced over 2 million tonnes of emissions
What You'll Do
You'll own analytics datasets and pipelines for specific product domains with real-world impact.
Our analytics engineers have full autonomy to drive the analytics direction for their areas – from defining success metrics to building self-serve capabilities. Join us in combining cutting-edge data engineering with purpose-driven analytics.
Technical Environment:
Modern Analytics Stack: SQL and Python in dbt on Airflow infrastructure
Data Warehouse Architecture: Dimensional data modelling for big data infrastructures - Modern distributed data warehouse solutions (Databricks experience a plus)
BI & Semantic Layer: Looker for semantic models and self-serve analytics
Orchestration: Airflow for pipeline automation and scheduling
Our Analytics Approach:
As a Senior Analytics Engineer, you will work as a collaborative partner. Working in a matrix organisation with 12 Analytics Engineers and 3 Platform Engineers, you'll build:
Easy to understand and consistently modelled datasets
Well-tested and documented data assets
Self-serve capabilities and user coaching
Best practices in data transformation pipelines
Close collaboration with software engineers on data capture
What You Need:
We expect you to be comfortable owning analytics infrastructure end-to-end, from defining key metrics with cross-functional partners to building production pipelines.
You'll value clean dimensional modelling, embrace testing and documentation as first-order concerns, and enjoy coaching others on self-serve analytics.
Required Experience
Dimensional data modelling for analytics / data warehouses / big data infrastructures
High proficiency in SQL (any dialect)
Programming in Python, Java or other language
Deep understanding of data warehouse technologies
Hands-on with BI tools such as Looker or Tableau
Track record using transformation tools such as dbt
Practical experience with orchestration systems such as Airflow
Strong communication skills with proven ability to explain technical concepts to non-technical audiences
Bonus Experience:
Databricks implementation or migration experience
Consumer-facing product analytics background.
Location & Benefits
Fully remote role within UTC -1 to UTC +3 time zones
Work with diverse teams across UK, Europe, and Africa
Professional development programs and coaching partnerships
Family-friendly policies and flexible working arrangements
Well-being support and career growth opportunities.