Data Modeller

The Data Modeller will contribute to the design, development, and implementation of high-quality data models to support the build of the Data Marketplace Data Domain and Product environment.

This individual contributor role focuses on leveraging Snowflake, industry-standard modelling techniques, DBT, and other applicable modelling tools to ensure scalable, efficient, and maintainable data solutions.

Key Accountabilities and main responsibilities

Strategic Focus

• Stay updated with industry trends and advancements in data modelling, Snowflake, and DBT.
• Identify opportunities for optimization and improvement using data modelling techniques.
• Drive complex technical transformations, decommissions and realising business outcomes through data and analytics.
• Drive the onboarding and rollout of technology services according to the pre-defined roadmap.
• Actively seek opportunities to develop skills and technical knowledge.

Operational Management

• Develop and maintain conceptual, logical, and physical data models using industry-standard modelling techniques.
• Design models to meet analytical, operational, and reporting requirements.
• Leverage Snowflake for cloud data modelling and architecture design.
• Utilize DBT (Data Build Tool) to manage data transformations and pipelines.
• Work with other applicable modelling software to enhance data workflows and output quality.
• Maintain thorough documentation of data models, data dictionaries, and related processes.
• Adhere to and promote best practices in data modelling and design.
• Collaborate with data & insight analysts, developers, and stakeholders to translate business requirements into robust data models.

Governance & Risk

• Ensure timely completion of activities by adhering with the agreed processes & quality standards.
• Individual should adhere to data design best practices.
• Adhere to MUFG’s standards, policies, and procedures.
• Adhere to data privacy and security standards (e.g., GDPR, HIPAA).
• Identify and mitigate security risks and ensure IT security design and delivery.

The above list of key accountabilities is not an exhaustive list and may change from time-to-time based on business needs.

Experience & Personal Attributes

Experience

• Overall, 5+ years of experience in data engineering and cloud migration in large, complex organisations with min 3+ years into data modelling
• Experience with Entity-Relationship (ER) diagrams for designing entities, attributes, and relationships.
• Knowledge of Object-Oriented Modelling (e.g., class structures, inheritance).
• Knowledge of Relational Database Management System (RDBMS) concepts
• Familiarity with Dimensional Modelling for analytics (facts and dimensions).
• Understanding of Business Process Modelling to link workflows and data entities.
• Proficient with data modelling tools like SqlDBM and Medallion Architecture(Bronze, Silver & Gold data layers) is preferable or with Erwin.
• Proficiency in Semantic Modelling for ontology-based data organization.
• Ability to translate conceptual models into logical database designs.
• Strong skills in defining data flows, dependencies, and relationships.
• Proficiency in normalization (1NF, 2NF, 3NF) for reducing redundancy and improving data integrity.
• Expertise in designing network and hierarchical models where needed.
• Experience translating logical models into database schemas.
• Knowledge of indexing, partitioning, and database optimization for performance.
• Familiarity with cloud-based database systems (e.g., Snowflake, Redshift).
• Proficiency in handling structured, semi-structured, and unstructured data.
• Star Schema design for simplified analytics and reporting.
• Snowflake Schema experience for storage optimization.
• Knowledge of Data Vault for historical tracking and scalability.
• Expertise in designing models for BI tools (e.g., Power BI, ThoughtSpot, Tableau).
• Experience with Graph Modelling for social networks, fraud detection, or interconnected data.
• Proficiency in Document Modelling (e.g., JSON, BSON) for NoSQL databases like MongoDB.
• Knowledge of Key-Value or Wide-Column Stores for NoSQL use cases.
• Familiarity with Temporal Data Models for handling time-variant or historical data.
• Proficiency in SQL for database design and query optimization.
• Familiarity with modern data platforms and tools: Erwin, ER/Studio, or similar for traditional modelling.
• Familiarity with collaborative design tools like Lucid chart, dbForge, or PowerDesigner.
• Experience with automation & cloud data platforms like Snowflake, AWS, Azure, or GCP.
• Strong understanding of data governance and metadata management.
• Hands-on experience with data integration and ETL/ELT processes.
• Ability to design scalable models for both OLTP (transactional systems) and OLAP (analytics systems).

Personal Attributes

• A dynamic and exceptional business-mind set with the ability to negotiate and influence senior level management, suppliers and key stakeholders.
• Exceptional skills in influencing and driving change across the organisation.
• Effective verbal and written communication skills, needed to communicate with global teams/stakeholders.
• Practical and simple problem-solving approach.
• Effective Team player with collaborative skills, learning and proactive attitude.
• Quality orientation with attention to detail.
• Commitment to continuous improvement.
• Excellent planning and organizational skills.
• Collaborate and share knowledge with other members of the team to ensure we are always evolving our collective skills and staying on the cutting-edge.
• Strong in developing presentations and the ability to present and capture a wide variety of audiences.
• Ability to expresses ideas effectively in individual and group situations; uses and shares information resources effectively.