Data Modeler

Job Description:

• Design, develop, and maintain logical and physical data models to support digital banking services, including real-time payments, onboarding/KYC processes, risk scoring, and customer 360 profiling. 

• Collaborate with Product Owners, Data Engineers, Business Analysts, and Compliance teams to translate regulatory and operational requirements into effective data structures. 

• Ensure data models support compliance with BSP Circulars (e.g., 1080 on data governance, 1122 on operational resilience), AML/KYC requirements, and consumer protection regulations. 

• Work closely with data warehousing and business intelligence teams to support the development of dashboards and analytics for business reporting, regulatory submissions, and marketing automation. 

• Perform data normalization, standardization, and deduplication to ensure data quality and minimize redundancy across systems (e.g., core banking, CRM, loan management, e-wallet). 

• Participate in the data governance council, supporting metadata management, data cataloging, and lineage tracking. 

• Evaluate and recommend data modeling tools and methodologies compatible with cloud-native environments such as AWS, Azure, or GCP, commonly used in digital banks. 

• Serve as a liaison between technical and non-technical stakeholders to ensure data models are both technically sound and business-aligned. 

Requirements

Required Skills and Competencies: 

• Strong proficiency in ER modeling tools such as Erwin, ER/Studio, or dbt (Data Build Tool). 

• Working knowledge of SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, DynamoDB) commonly used in modern digital architectures. 

• Familiarity with data mesh, data lakehouses, and cloud-native architectures in a regulated fintech environment. 

• Hands-on experience with data integration tools, ETL pipelines, and API-based data exchange frameworks. 

• Deep understanding of relational and dimensional modeling for both transactional and analytical systems. 

• Knowledge of data privacy and data residency rules in the Philippines and how they impact model design. 

• Experience working with CI/CD pipelines and version control tools (e.g., Git, Bitbucket) for data-related assets. 

Qualifications: 

• Bachelor’s Degree in Computer Science, Information Systems, Data Science, or a related field. Master’s Degree is a plus. 

• 4–6 years of experience in data modeling and analysis, preferably in banking, fintech, or digital financial services. 

• Experience working in Agile or Scrum environments, with a strong focus on cross-functional collaboration.