Job Title: Senior Analytics Engineer – Financial Inclusion at Scale
Organisation: M-KOPA
Duty Station: Kampala, Uganda
About Organisation:
The scale and impact of our work is massive. M-KOPA is a fast-growing Fin Tech 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.
Job Summary: 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 🌍
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.
Qualifications, Skills and 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
How to Apply:
All candidates should apply online at the link below.
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Level of Education: Bachelor Degree
Work Hours: 8
Experience in Months: no experience required