Data Modeller

**Overview**

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.

People Leadership
- 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, 10+ years of experience in data engineering and cloud migration in large, complex organisations with min 6+ 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).
- Familiarity with Dimensional Modelling for analytics (facts and dimensions).
- Understanding of Business Process Modelling to link workflows and data entities.
- 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., Tableau, Power BI, ThoughtSpot).
- 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 gl