Senior Data Modeller

Job description

**Overview** The Senior Data Modeller is responsible for designing, implementing, and optimizing data models that support analytical, operational, and reporting needs. This role ensures that data models are scalable, high-performance, and aligned with business requirements, enabling efficient data management and utilization. The Senior, Data Modeller collaborates with data engineers, architects, and business stakeholders to establish best practices in data modelling, metadata management, and data governance to enhance data integrity and accessibility **Key Accountabilities and main responsibilities** Strategic Focus - Develop and maintain conceptual, logical, and physical data models to support business operations and analytics. - Ensure that data modelling solutions align with enterprise architecture and business objectives. - Identify opportunities for optimizing data structures, improving query performance, and ensuring scalability. - Support data integration efforts by designing models that enable seamless data movement and accessibility. - Drive best practices in metadata management and data lineage tracking. Operational Management - Work with data engineers to implement and maintain data models in cloud-based and on-premises environments. - Optimize data models to enhance performance, reduce redundancy, and improve efficiency. - Collaborate with stakeholders to define data definitions, relationships, and standards. - Develop documentation and training materials for data modeling frameworks and best practices. - Conduct reviews and validation exercises to ensure data models meet business and technical requirements. People & Leadership: - Demonstrate strong leadership and relationship building - Illustrate confident decision making - Ensure alignment with key stakeholders - Collaborate with data & insight analysts, Technical Analysts, developers and testers to translate business requirements into robust data models. Governance & Risk - Ensure compliance with data governance, security, and regulatory requirements in data modelling. - Maintain comprehensive documentation for data models, lineage, and versioning. - Work with governance teams to enforce data standards, quality controls, and compliance policies. - Adhere to data privacy and security standards. Demonstrate strong awareness and adherence to PII (Personally Identifiable Information) standards, ensuring compliant handling, protection, and governance of sensitive data across all processes. - Support audits and risk assessments related to data modelling practices. **Experience & Personal Attributes** Experience - Overall 8+ years of extensive experience in data modelling, database architecture, and metadata management. - Strong proficiency in SQL, data modelling tools, and cloud data platforms. - Deep understanding of data governance, data quality, and compliance frameworks. - Proficient with SqlDBM and Medallion Architecture(Bronze, Silver & Gold data layers) is preferable or with Erwin. - 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. - 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). - Proven ability to drive organizational change and influence outcomes effectively. Personal Attributes - Excellent problem-solving and analytical skills. - Effective communication and collaboration skills to work with technical and business teams. - Ability to work in a fast-paced, data-driven environment. - 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 ca