Data Architect

Position Title : Data Architect

Department : IT Data and Analytics

Location : National Capital Region, Philippines

Employment Type : Full-time, Onsite

Overview

The IT Data and Analytics department is a critical enabler for the effective use of data platforms and AI by managing data architecture and providing scalable data and AI solutions. This role empowers the bank to leverage insights for strategic decision-making, customer personalization, and risk management.

Key Responsibilities

Data Model Design

Develop and maintain conceptual, logical, and physical data models within the Enterprise Data Platform using tools like Erwin Data Modeler.

Design data structures optimized for performance, scalability, and maintainability.

Data Integration & Mapping

Define and document data mappings for ETL processes and integration across multiple components using Azure Data Factory and Azure Databricks.

Data Access & Security

Implement and manage Unity Catalog for metadata management and access control.

Ensure compliance with internal and external data security and privacy standards.

Performance Optimization

Optimize data models for query performance, scalability, and storage efficiency.

Apply techniques like partitioning and indexing.

Metadata Management

Manage and track metadata across data models within the Enterprise Data Platform.

Collaboration

Work closely with data engineers, business analysts, and IT teams to translate business requirements into technical data designs.

Version Control & Documentation

Manage version control for data models and maintain data dictionaries, ERDs, and technical documentation.

Qualifications

Education : Bachelor’s degree in Computer Science, Information Technology, or related field.

Experience : 5–7 years in data architecture, data modeling, and enterprise data platforms.

Technical Skills :

Proficient in data modeling tools (e.g., Erwin Data Modeler).

Experience with Azure Data Factory, Azure Databricks, Unity Catalog.

Strong knowledge of ETL processes, SQL, and performance tuning techniques.

Soft Skills : Strong analytical, problem-solving, and stakeholder management skills.

Preferred Competencies

Familiarity with data governance frameworks.

Knowledge of AI / ML data requirements.

Ability to work in agile environments.