Supervisor - Data Engineering

Reporting to the Assistant Manager – Data Engineering, the successful candidate will support the Credit Risk Insights, Research and Analytics Unit by developing and maintaining analytical tools that transform risk models and manual reporting processes into reliable, automated and auditable applications.

The role focuses on developing valuation tools, business calculators, automated reports, data pipelines and Power BI dashboards that support informed business decisions. The successful candidate will work closely with analysts, business users and IT to translate business requirements into practical, well-documented technical solutions.

Key Responsibilities

Automation, Modelling & Analytical Solutions

• Assist in designing, developing and maintaining automated valuation tools, including property valuation models.
  

• Develop calculators and analytical tools to support pricing, profitability and other business decisions.
  

• Automate recurring reports and data processes to reduce manual effort and improve accuracy.
  

• Build and maintain Power BI dashboards and reports for management and business users.
  

Data Architecture & Engineering

• Develop and maintain data pipelines to collect, clean and integrate data from internal and external sources.
  

• Build and manage data warehouses, data lakes and data marts.
  

• Optimise data storage, retrieval and processing for large datasets.
  

• Implement appropriate data validation, testing and documentation to support reliable data solutions.
  

Stakeholder Engagement & Solution Development

• Gather stakeholder requirements and translate them into effective technical solutions.
  

• Enhance existing tools, spreadsheets and reports in response to user feedback and business needs.
  

• Collaborate with IT on data access, infrastructure and solution deployment.
  

• Keep abreast of emerging technologies and recommend improvements to tools and processes.
  

Audit, Governance & Data Quality

• Implement validation and reconciliation checks to support data accuracy and reliability.
  

• Monitor, investigate and resolve data anomalies, escalating issues where necessary.
  

• Maintain clear documentation of data pipelines, processes and technical solutions.
  

• Ensure compliance with applicable governance, regulatory and internal standards.
  

• Provide supporting data and documentation for audit and review requests.
  

Collaboration & Business Support

• Collaborate with Data & Analytics, Credit, Risk and Audit teams to deliver assigned projects and analytical solutions.
  

• Contribute to monthly reporting, presentations and other related assignments.
  

• Maintain effective communication with stakeholders and ensure deliverables meet agreed timelines and quality expectations.
  

Qualifications & Experience

The ideal candidate should possess:

• A Bachelor’s Degree in Computer Science, Software Engineering, Data Science, Mathematics or a related field.
  

• At least three (3) years’ experience developing data-driven applications, analytical tools or reporting solutions.
  

• Strong programming skills, preferably in Python.
  

• Good SQL and database skills.
  

• Experience developing dashboards using Power BI or a similar business intelligence tool.
  

• Experience building web-based applications or business tools.
  

• Experience automating data and reporting processes.
  

• Familiarity with version control and software development best practices.
  

• Advanced Microsoft Excel skills.
  

• The ability to explain technical concepts and solutions clearly to non-technical users.
  

Key Competencies & Skills

The successful candidate will demonstrate:

• Strong analytical and critical-thinking skills.
  

• Achievement orientation and a commitment to continuous improvement.
  

• Innovation and the ability to identify opportunities for more efficient technical solutions.
  

• Flexibility and adaptability in responding to changing business requirements.
  

• Effective communication, interpersonal and relationship-building skills.
  

• Strong organisational skills, including the ability to multitask and prioritise competing assignments.
  

• The ability to work independently, exercise sound judgement and make appropriate decisions.
  

• A collaborative approach to working with technical and non-technical stakeholders.