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Senior BI Engineer

Mama Money


Job Location:

Cape Town - South Africa

Monthly Salary: Not provided by the employer
Posted: 29 May 2026 (30+ days ago)
Application Deadline: 14 September 2026
Vacancies: 1 Vacancy
The job posting is outdated and position may be filled

Job Summary

Who we are:

Mama Money is a growth-stage fintech on a mission to improve the financial lives of migrants and underserved communities across Africa and beyond. What started in 2015 as a cross-border payments service has grown into a multi-product financial platform. We give people the tools to send save and manage money on their own terms at a socially fair price.

Mama HQ is in beautiful Cape Town South Africa. Were 153 people strong (and counting) representing 19 countries across Africa Asia the UK and Europe. From remittances to a growing range of financial products everything we build is in service of people who deserve better. Our culture reflects that same commitment. We look after our team the way we want them to look after our customers. Just be lekker! means we trust our talented diverse people to do whats right and make it happen simply and with heart.

Weve earned a few accolades built lasting partnerships and grown our reach in ways were proud of. Weve had good times and tough times but our focus has never shifted. People over profit always.

Were looking for a Senior BI Engineer to join our Data team and become a key driver of how data is structured surfaced and used across Mama Money. This role goes beyond analysis youll design and build the data products models and reporting layers that enable fast reliable self-service decision-making across the business.

As our Senior Bi Engineer you will:
  • Design and build scalable data models (dimensional models semantic layers and curated datasets) that power reporting and analytics across the business.

  • Own the development and optimisation of BI dashboards and reporting layers ensuring they are accurate performant and self-service ready.

  • Partner with Data Engineering to define data contracts improve data quality and ensure robust well-structured pipelines.

  • Translate complex ambiguous business requirements into well-defined data models and BI solutions.

  • Build and maintain cohort funnel retention and performance datasets that enable consistent reporting across teams.

  • Support experimentation by ensuring A/B test data is correctly structured tracked and accessible for analysis.

  • Develop and maintain KPI definitions metric layers and a single source of truth for core business metrics.

  • Work closely with stakeholders to design dashboards that go beyond reporting enabling real decision-making.

  • Perform deep-dive analysis into customer behaviour churn fraud patterns and commercial performance when needed.

  • Champion data governance documentation and consistency in how data is defined and used across the organisation.

  • Identify opportunities to improve data architecture reporting efficiency and self-service capability.

  • Stay close to the customer journey and ensure data reflects real-world product and user behaviour accurately.

Youll be working with (or alongside) a stack that includes:
  • Cloud & infrastructure: AWS (EKS EC2 S3) Kubernetes Terraform

  • Data ingestion & processing: AWS DMS EMR EC2-based pipelines writing to S3

  • Querying & modelling: Athena dbt SQL throughout (strong emphasis on modelling layers)

  • Reporting & BI: Tableau as primary BI tool (with focus on semantic layer and dashboard design)

  • Analysis & scripting: Python (Pandas statsmodels etc) for deeper analytical work

  • Product & customer tooling: Zendesk internal CRM systems product analytics platforms

  • Ways of working: Agile squads cross-functional collaboration async documentation-first culture

Qualifications and experience:
  • 5 years experience in a BI Engineer Analytics Engineer or Data Analyst role in fintech SaaS or other high-volume consumer environments

  • Strong SQL skills with experience in building and optimising data models and transformations

  • Hands-on experience with dbt or similar transformation frameworks

  • Strong BI experience (Tableau preferred or Power BI / Looker / Metabase) with a focus on scalable dashboarding and semantic design

  • Solid understanding of data modelling principles (star schema facts/dimensions metric consistency)

  • Experience supporting or enabling experimentation frameworks (A/B testing metric tracking data readiness)

  • Strong analytical ability with Python or R for deeper investigation work

  • Proven ability to turn complex business needs into structured maintainable data solutions

  • Strong stakeholder management skills across technical and non-technical teams

  • Ability to balance engineering discipline business storytelling building trusted data products not just reports

Why Mama Money

At Mama Money were here to make it easyfor our customers our communities and for each other. Simplicity is at the heart of what we do whether its creating a seamless and stress-free customer journey or removing barriers that stand in the way of progress our work is all about delivering impact minimizing complexity and ensuring every experience with Mama Money is easy.

Were a team that isnt afraid to give it a go. We value taking action making bold steps embracing innovation solving problems doing the hard things and thinking smartly. Mistakes and failures dont stop usthey teach us. Every challenge is a chance to grow do better and push boundaries.

And we just own it. Whether its delivering results collaborating across teams driving urgency or taking accountability for our actions we approach every task with integrity and purpose. We make company goals our own showing up for each other our customers and our mission to create lasting change.

Mamas Values

These arent just wordstheyre how we show up every day:

  • Make it easy for customers

  • Give it a go

  • Just own it

We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.

Required Experience:

Senior IC


About Company

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