Watu Credit Limited is looking for a proactive technical lead to stabilize and develop core systems while engineering automated AI and ML solutions. As a Senior Analytics Engineer, you will play a defining role in our technical legacy, transitioning models from notebooks into reliable production environments and overseeing the global data architecture.
Key Responsibilities
Lead Data Architecture & Pipelines: Architect, deploy, and oversee robust end-to-end ingestion frameworks. Ensure raw data from diverse sources is reliably integrated into our Data Warehouse using cloud-native tools (Datastream, Fabric, Spark).
Advanced Data Transformation: Own the modeling layer by designing complex, performant transformation logic using dbt and SQL. Establish standards for clean, version-controlled, and analyst-ready datasets.
MLOps & Model Productionalization: Bridge the gap between research and production by engineering the pipelines required to deploy Machine Learning models and AI agents. Transition models from notebooks into stable, automated, and monitorable production workflows.
Data Quality & Technical Governance: Act as the primary guardian of data integrity. Define and enforce strict security protocols, data quality tests, and governance rules to ensure consistency and compliance across the global organization.
Warehouse & Infrastructure Excellence: Manage the administration of the Data Warehouse (BigQuery/Fabric), optimizing for performance, cost-efficiency, and scalability. Select and maintain Analytics Engineering tooling.
Intelligent Automation: Lead the development of internal AI tools and "intelligent workflows" to solve complex business logic challenges.
Technical Leadership & Mentorship: Define engineering best practices (CI/CD, documentation, modularity) and provide guidance to team members on the long-term evolution of the data strategy.
Requirements
Experience: At least 5 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 (specifically for data manipulation, automation, and API integrations).
Data Architecture: Deep expertise in modern Data Warehouse design (BigQuery, Microsoft Fabric), dimensional modeling, and implementing scalable architectural patterns.
Modern Data Stack: Extensive hands-on experience with the ELT/ETL lifecycle, including advanced transformation workflows using dbt (Data Build Tool) and orchestration.
Cloud Infrastructure: Strong proficiency with Google Cloud Platform (GCP)—specifically BigQuery, Datastream, and Dataflow—and experience with Spark for large-scale data processing.
Software Excellence: A strong proponent of engineering best practices, including Git version control, CI/CD pipelines, and writing clean, maintainable, and well-tested code.
Education: BA/BSc/HND degree.
How to Apply
Interested and qualified candidates should apply online via the Watu Credit Limited portal on watu.applytojob.com. Alternatively, applications can be submitted through the MyJobMag application link.
