Data Engineer

Main Purpose of Job

• Gather, extract data, review, monitor and identify consumer, collection, key trends in overall credit portfolio data and provide data insights, data-driven solutions to support credit and business policies as well as strategies for productivity, profitability and efficiency improvement.
• support the development and automation of data pipelines for credit risk assessment. This role plays a critical part in enabling accurate, timely, and scalable credit risk analytics by ensuring robust data availability, quality, and processing efficiency.

Principle responsibilities & duties

• Design, develop, and maintain scalable data pipelines to support credit risk assessment and model input preparation.
• Integrate data from multiple internal and external sources (e.g., LOS, CBS, CCRIS ) into a centralized data warehouse or data mart environment.
• Ensure data gathering and extraction are done on timely basis for insights and data-driven solutions to be shared on timely basis to management in a succinct and usable format
• Implement data quality checks, cleansing routines, and transformation logic to ensure accurate and reliable outputs.
• Automate data extraction, transformation, and loading (ETL/ELT) workflows for recurring credit risk reporting and analysis.
• Monitor and troubleshoot data workflows and implement enhancements for performance optimization.
• Be a good leader and coach to the team.
• Work closely with relevant stakeholders to obtain necessary data and understanding of the processes as well as business strategies to support the overall solutions to be provided to management.

Minimum job requirement (education & experience)

• 2–3 years of experience in data engineering, preferably in a financial or risk analytics environment.
• Proficiency in SQL, Python, and ETL frameworks (e.g., Apache Airflow, Talend, AWS Glue).
• Experience with cloud platforms such as AWS, Azure, or GCP (particularly S3, Redshift, or BigQuery).
• Experience with version control (e.g., Git) and CI/CD pipelines is a plus.
• Good leadership and management skills with the ability to train and develope team members
• Strong analytical skills to study, review credit portfolio and translate this to solutions to management
• Possess effective communication and written skills
• Ability to work in a fast-paced and evolving organization

Knowledges, skills and abilities required

• Strong understanding of Credit operations and processes.
• Knowledge of Credit policy and data analysis, pipeline development lifecycle.
• Excellent communication, and interpersonal skills.
• Analytical mindset with the ability to analyze data and draw meaningful insights.
• Strong problem solving and decision-making abilities.
• Detail-oriented with excellent organization and multitasking skills.

Job competency requirements

• Proven knowledge of using data science toolkits such as Python, R, SQL, Tableau, etc
• Good understanding of machine learning algorithms

Essential/Desirable personality attributes/qualities/traits

• Adaptable: Ability to thrive in a dynamic work environment.
• Team Player: Collaborate effectively with cross-functional teams
• Proactive: Proactive and innovative mindset with a focus on continuous improvement