We are looking for a talented Data Engineer to join our Credit Risk team and contribute to optimizing data pipelines, enhancing analytical capabilities, and ensuring data integrity across critical credit risk models.

About the role

As a Data Engineer within our Credit Risk team, you will play a crucial role in designing, developing, and maintaining data infrastructure that supports our credit risk modeling efforts. You will work closely with Quantitative modelers, model experts, and other stakeholders to ensure the availability, accuracy, and reliability of data used in our credit risk models.

Data Engineer role also involves:

• Data Pipeline Development: Design, develop, and maintain scalable, efficient data pipelines to support credit risk modelling, analysis and reporting.

• Collaboration with Quantitative modelers and product experts: Work closely to ensure the data infrastructure supports the development of predictive credit risk models.

• Data Quality & Governance: Collaboration with Data stewards to ensure high-quality, accurate, and consistent data for credit risk modeling and reporting.

• Data Integration & Management: Integrate data from various internal and external sources into a unified data ecosystem.

• Automation & Optimization: Automate and optimize data processes to enhance the efficiency and accuracy of reporting and risk assessments.

To thrive in this role, we believe you have:

• Proven experience in a Data Engineer or in a similar role, preferably within the financial sector.

• Technical Expertise: Proficient in SQL, Python, and data modelling techniques and working with large datasets.

• Data Warehousing: Knowledge of data warehousing concepts and best practices for data integration and storage.

• Data Governance: Strong understanding of data quality, security, and governance best practices.

• Problem Solving: Ability to solve complex problems and attention to detail.

• Communication: Strong communication skills with the ability to collaborate across teams, both technical and non-technical.

• Risk Management Understanding: Familiarity with credit risk, Basel III, and other financial risk frameworks is a plus.

Preferred qualifications:

• Degree: Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.

• Experience in Credit Risk: Experience with risk models, including credit scoring, financial regulations, and portfolio analysis, is highly desirable.

• Strong analytical skills and the ability to work with complex datasets.

• Experience with version control systems (e.g., Git).