Data Engineer

• 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 supporting business intelligence, analytics and AI solutions
• Implement data quality controls, reconciliation, metadata, lineage and monitoring mechanisms
• Apply data security, privacy, access controls, encryption and retention requirements in line with the Data Protection Act, 2019 and Bank policies
• Optimise data pipelines for performance, reliability, scalability and cost, ensuring recovery, auditability and resilience
• Translate business requirements into fit-for-purpose datasets together with business data owners
• Integrate automated testing, source control and CI/CD practices into data engineering workflows
• Monitor production pipelines, troubleshoot incidents, resolve defects and maintain technical documentation
• Develop ingestion and processing pipelines for unstructured data such as documents, text and voice to support generative AI applications and vector databases

Qualifications & Experience:

• 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 is an added advantage
• Experience in banking, financial services or another regulated data environment is an added advantage

Skills & Competencies:

• Data pipeline design and performance tuning
• Data quality, lineage and metadata management
• Automation and CI/CD practice
• Clear documentation and teamwork