Kuda is a money app for Africans on a mission to make financial services accessible, affordable and rewarding for every African on the planet.
We’re a tribe of passionate and diverse people who dreamed of building an inclusive money app that Africans would love so it’s only right that we ended up with the name ‘Kuda’ which means ‘love’ in Shona, a language spoken in the southern part of Africa.
We’re giving Africans around the world a better alternative to traditional finance by delivering money transfers, smart budgeting and instant access to credit through digital devices.
We’ve raised over $90 million from some of the world's most respected institutional investors, and we’re rolling out our game-changing services globally from our offices in Nigeria, South Africa, and the UK.
Role Overview
We are expanding our reach and seeking a visionary Senior Data Engineer to spearhead our data engineering efforts, driving innovation and growth. With a passion for data-driven decision-making, you will play a pivotal role in shaping the future of banking for millions.
Roles and responsibilities
- Design, develop, and optimise large-scale data ingestion, transformation, and processing pipelines for structured, semi-structured, and unstructured data.
- Lead the integration of multi-cloud and hybrid data platforms (e.g., Azure SQL, Google BigQuery, on-premises SQL Server).
- Define and enforce data architecture standards to ensure scalability, security, and optimal performance.
- Leverage Dataform to manage SQL-based transformations, version control, testing, and deployment of analytics datasets in BigQuery.
- Introduce and manage real-time streaming solutions (e.g., Kafka, Pub/Sub, or Dataflow) in conjunction with batch data pipelines.
- Data Quality & Governance
- Establish data quality frameworks with automated validation, anomaly detection, and reconciliation checks.
- Collaborate with Data Governance teams to maintain data catalogues metadata management, and lineage tracking.
- Implement security, privacy, and compliance standards (such as GDPR, NDPR, and ISO 27001) within data pipelines.
- Mentor junior and mid-level data engineers, providing technical guidance and career development support.
- Partner with Data Science and BI teams to deliver data products for predictive modelling, experimentation, and self-service analytics.
- Act as a subject matter expert in cross-functional projects, advising on technical trade-offs and best practices.
- Research and adopt emerging data engineering technologies and methodologies.
- Drive automation in data workflows to reduce manual intervention and operational risk.
- Optimise data storage and compute costs through partitioning, clustering, and workload management.
