Data Analyst

Responsibilities

• Data Extraction, Transformation & Automation
• Extract, clean, validate, and reconcile data from multiple source systems, including finance datamarts, GL, product systems, customer-level datasets, and business reports.
• Build automated data pipelines and repeatable reporting templates to reduce manual reporting effort.
• Support automation of recurring reports such as monthly performance tracking, forecast packs, product P&L, cost reports, and variance.
• Dashboard & Reporting Development
• Develop Power BI / Excel dashboards to provide timely visibility on business performance, product profitability, sales trends, cost movements, and KPI tracking.
• Translate business requirements into clear data models, dashboards, and self-service reporting tools.
• Ensure dashboards are user-friendly, accurate, and aligned with management reporting needs.
• Financial & Business Analysis
• Support Business Finance teams in analysing revenue, cost, margin, NIM, FTP, fee income, product profitability, and customer segment performance.
• Assist in budget, forecast, and scenario modelling by preparing clean datasets and analytical views.
• Perform trend analysis, variance analysis, root cause analysis, and business driver analysis to support management decision-making.
• Product P&L Support
• Support development of product-level and account-level P&L reporting by preparing, validating, and reconciling data inputs.
• Work with Finance, Business, IT, and vendors to ensure data logic, mapping rules, and reconciliation processes are properly documented.
• Assist in identifying data gaps, product ownership issues, and exception handling required for product P&L reporting.
• Data Governance & Quality Control
• Perform data quality checks, reconciliation, and exception reporting to ensure accuracy and consistency of outputs.
• Document data definitions, transformation logic, assumptions, and report methodologies.
• Maintain a structured repository of reports, data logic, dashboards, and working files.
• Stakeholder Support
• Work closely with Finance Business Partners, Product Managers, Business Heads, IT, Analytics, and external vendors.
• Translate business questions into data requirements and analytical outputs.
• Provide clear commentary and insight to support management presentations, business reviews, and decision papers.

Requirements

• Education
• Degree in Data Science and Business Analytics, Computer Science, or related field.
• 6-10 years experience in banking finance, finance systems, or financial data management
• Technical Knowledge
• Understanding of data warehouse architectures, and database structures
• Knowledge of SQL or data querying tools
• Familiarity with analytics platforms such as Power BI or Tableau
• Project & Vendor Experience
• Experience implementing finance data warehouse or finance datamart in banking.
• Familiarity with product profitability, FTP allocation, and banking financial data structures.
• About Hong Leong Bank
• Realise your full potential at Hong Leong Bank by applying now.

Additional Information

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