SRT Data Architect & Analyst

ING Bank Personeel; Makati; On-site; PHP 800,000 - 1,600,000; Full time

Job summary

ING Bank Personeel is seeking a Data Analyst to design, develop, and maintain the data foundation for Significant Risk Transfer (SRT) within Wholesale Banking. The role bridges business and technology, turning complex requirements into scalable data models with governance and traceability across lending and risk platforms.

The successful candidate will work with Risk, Finance, Capital Management, Data Management, and Technology teams to deliver high-quality data solutions supporting regulatory

Qualifications

• Strong experience in data analysis and data modelling.
• Advanced SQL skills and data mapping, reconciliation, and quality management.
• Knowledge of Wholesale Banking lending data environments.
• Experience delivering complex data analysis or data modelling initiatives in regulated or business-critical environments.

Responsibilities

• Designing conceptual, logical, and physical data models for SRT.
• Translating business requirements into data requirements and source-to-target mappings.
• Analyzing and integrating data across Wholesale Banking lending systems such as LoanIQ, GRID, and Vortex.
• Establishing data lineage, reconciliation processes, and quality controls.
• Performing data analysis and prototyping using SQL and analytical tools.
• Collaborating with cross-functional stakeholders across Risk, Finance, Technology, and Data Management.
• Creating and maintaining documentation, metadata, and decision logs.
• Supporting implementation, testing, and operationalization of data solutions.

Skills

Data analysis

Data modelling

Advanced SQL

Stakeholder management

Communication skills

Analytical thinking

Tools

LoanIQ

GRID

Vortex

Job description

ING Bank Personeel is seeking a Data Analyst to design, develop, and maintain the data foundation for Significant Risk Transfer (SRT) within Wholesale Banking. The role bridges business and technology, turning complex requirements into scalable data models with governance and traceability across lending and risk platforms.

The successful candidate will work with Risk, Finance, Capital Management, Data Management, and Technology teams to deliver high-quality data solutions supporting regulatory