- Cape Town
- Salary: Market Related
- Job Type: Permanent
- Sectors: Investment Technology
- Reference: 184887
Vacancy Details
Employer: Lesaka Technologies
Senior Analytics Engineer – Cape Town
We’re building the future of financial services in Southern Africa.
At Lesaka, our mission is to make financial services accessible, scalable, and efficient for businesses and consumers. Data sits at the heart of how we price, manage risk, optimise revenue, and scale sustainably.
We’re building a modern, scalable data platform — and we’re looking for a Senior Analytics Engineer to help us define and build the core analytics layer that the business runs on.
🚀 Your Mission
Your mission is simple:
Build trusted, scalable data models that enable better decisions — and empower teams to self-serve data confidently.
You’ll work across Product, Finance, Risk, and Operations to turn complex data into reliable, well-structured datasetsthat are easy to use and widely adopted.
🛠 What You’ll Be Doing
Build Scalable Analytics
- Develop and maintain dbt models across staging, intermediate, and marts
- Structure transactional and financial data into clean, reusable datasets
- Write and optimise SQL in BigQuery (performance + cost)
- Work with Data Engineering on pipelines (e.g. Airflow)
Enable Self-Service Analytics
- Design datasets that are intuitive, well-documented, and easy to use
- Reduce reliance on raw tables and ad hoc SQL
- Ensure consistent, trusted data for Looker / BI consumption
- Help teams answer questions independently without needing constant data support
Own Data Quality & Metrics
- Define and standardise core KPIs (single source of truth)
- Implement data tests and validation frameworks
- Ensure consistency across finance, product, and operational reporting
Partner with the Business
- Work closely with Product, Finance, Risk, and Operations teams
- Translate business requirements into scalable data models
- Support better decision-making through trusted data foundations
Raise the Bar
- Improve data modeling standards and best practices
- Contribute to better documentation, lineage, and discoverability
- Reduce manual reporting and fragmented logic across teams
🧠 What You’ll Bring
- 5+ years experience in Analytics Engineering, Data Engineering, or BI
- Advanced SQL skills (complex transformations, optimisation)
- Experience with dbt in production
- Experience with BigQuery or modern cloud data warehouses
- Strong data modeling skills (facts, dimensions, grain)
Senior Expectations
- Comfortable working cross-functionally with senior stakeholders
- Able to take ambiguous problems and turn them into structured solutions
- Strong ownership — you care about data quality, usability, and outcomes
- Able to influence standards and best practices
- Clear communicator — able to explain data simply and effectively
Bonus if you have
- Experience in fintech, payments, or financial services
- Exposure to Airflow or orchestration tools
- Experience working with large-scale transactional datasets
- Interest in AI/ML use cases built on strong data foundations
🤖 AI & LLMs (Nice to Have)
- Exposure to modern AI/LLM tools such as Claude or similar large language models
- Experience using LLMs to improve analytics workflows (e.g. SQL generation, documentation, data exploration)
- Interest in how well-structured data models enable downstream AI/ML and LLM use cases
- Familiarity with embedding analytics datasets into AI-driven applications or decision-support tools
🤝 What We’re Looking For
We’re not looking for someone to just move data.
We’re looking for someone who:
- Takes ownership
- Is comfortable with ambiguity
- Thinks about scalability and reuse
- Builds for self-service, not dependency
- Cares about data being trusted and widely used
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