Data Modeller

Job description

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. • 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. 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