Data Engineer at Co-operative Bank of Kenya

The Role

Specifically, the successful jobholder will be required to:

• Design, develop, test and maintain batch, streaming and real-time data pipelines that integrate data from approved source systems into the Bank’s data and AI platforms.
• Build reusable, well-structured data products and feature sets that support business intelligence, analytics, AI solutions and informed decision-making.
• Implement data quality controls, reconciliation, metadata, lineage and monitoring mechanisms to ensure data accuracy, completeness, consistency and timeliness.
• Apply data security, privacy, access controls, encryption and retention requirements in line with the Data Protection Act, 2019, and the Bank’s policies and standards.
• Optimise data pipelines for performance, reliability, scalability and cost, ensuring effective recovery, auditability and operational resilience.
• Collaborate with cross-functional teams and business data owners to translate business requirements into fit-for-purpose datasets and data solutions.
• Integrate automated testing, source control and CI/CD practices into data engineering workflows, supporting deployments across development, testing and production environments.
• Monitor production pipelines, troubleshoot incidents, resolve defects and maintain technical documentation and operating procedures.
• Develop data ingestion and processing pipelines for unstructured data, including documents, text and voice, to support generative AI applications and technologies such as vector databases.

Skills, Competencies and Experience

The successful candidate will be required to have the following skills and competencies:

• A bachelor’s degree in Computer Science, Information Technology, Engineering, Data Science, Mathematics or a related field.
• At least four (4) years of relevant experience in data engineering, ETL/ELT development, database engineering or big-data implementation.
• Hands-on experience building and supporting production data pipelines and curated analytical datasets.
• Strong proficiency in SQL and Python, Scala or comparable programming languages.
• Professional certification in data engineering, cloud data platforms, databases or analytics will be an added advantage.
• Experience in banking, financial services or another regulated data environment will be an added advantage.