Watu Credit Limited is a dynamic and fast-growing non-bank finance company. Watu Credit Limited harnesses technology to offer unsecured lending, primarily via mobile services. We aim to become the leading African provider of a broad set of inclusive financial products, delivered through technology in a fast, efficient and professional manner. Key Responsibilities: Build & Deploy Pipelines: Design, create, and deploy robust data ingestion pipelines to continuously feed the Data Warehouse with raw data from diverse sources using cloud-hosted ingestion tools. Data Transformation: Create and maintain efficient processes to transform raw data into clean, organized, and analyst-ready datasets using dbt, SQL, and Google Cloud tools (Dataflow, Datastream). Data Quality & Security: act as the guardian of the Analytics data, taking full responsibility for data quality, consistency, and the implementation of strict security protocols. Governance Implementation: Define and implement data governance rules to ensure data integrity and compliance across the organization. Warehouse Administration: Manage the administration of the Data Warehouse, ensuring optimal performance, organization, and accessibility. Tooling & Infrastructure: Implement, develop, and maintain the necessary Analytics Engineering tools and infrastructure to support the wider data team. Architecture Support: Actively assist in defining and evolving the data architecture to ensure it remains scalable and efficient as the business grows. AI Development & Automation: Work on the company’s initial AI initiatives by developing custom agents, tools, and intelligent workflows that leverage our data foundation to automate complex business processes. Requirements: Knowledge, Skills, and Experience: Experience: At least 3 years of proven experience working in a Data Engineering or Back-end Engineering role. Core Languages: Advanced proficiency in SQL and strong coding skills in Python. Data Warehousing: A deep understanding of modern Data Warehouse technologies, architectural patterns, and industry best practices. Data Operations: Expertise with the latest tools and processes for data ingestion, transformation, and management (ETL/ELT).
