Data Modeller

Data Modeling Design: Design and maintain conceptual, logical, and physical data models to support transactional, analytical, and data warehousing systems. Develop data models to ensure data consistency, integrity, and quality across multiple banking functions and applications. Define and implement the best practices for data modeling, data integration, and metadata management. Data Architecture Collaboration: Collaborate with data architects to align models with enterprise data architecture and ensure optimal performance and scalability. Work with database administrators to translate logical models into physical database structures and optimize them for performance. Data Quality Governance: Establish data standards, definitions, and quality rules to ensure data accuracy, consistency, and compliance. Create and maintain data dictionaries and metadata repositories to support data governance and facilitate efficient data access. Stakeholder Engagement: Engage with business stakeholders, data scientists, and IT teams to understand data requirements and translate business needs into robust data models. Ensure data models support key business initiatives, such as regulatory reporting, analytics, and operational efficiency. Documentation Best Practices: Develop and maintain detailed documentation, including data models, entity-relationship diagrams, and mapping specifications. Implement data modeling standards and mentor team members to promote best practices in data management. Requirements: Educational Qualification: MBA / Engineering degree with relevant industry experience. Experience: Minimum of 10 years of experience in data modeling or as a data modeler within the banking industry. Proven expertise in designing data models across at least three of the following areas: Data Warehousing Analytics BI Data Mining Data Quality Metadata Management Technical Skills: Proficiency in data modeling tools such as Erwin, IBM InfoSphere, or SAP PowerDesigner. Strong SQL skills and experience in relational database systems like Oracle, SQL Server, or DB2. Familiarity with big data technologies and NoSQL databases is a plus. Knowledge of ETL processes and tools (e. g. , Informatica, Talend) and experience working with BI tools (e. g. , Tableau, Power BI). Knowledge of SAS for analytics, data manipulation, and data management is a plus. Strong understanding of data governance frameworks, data quality management, and regulatory compliance. Soft Skills: Strong analytical and problem-solving skills, with attention to detail and accuracy. Excellent communication and interpersonal skills, with the ability to translate technical data concepts for business stakeholders. Proven ability to work collaboratively in a cross-functional environment and manage multiple projects.