Job description
Role Summary We are looking for an experienced Data Modeler to design, develop, and maintain scalable enterprise data models that support business, analytics, reporting, and data platform requirements. The role will work closely with business stakeholders, Data Architects, Data Engineers, BI teams, and application teams to translate complex business requirements into well-structured conceptual, logical, and physical data models. The ideal candidate should have strong expertise in dimensional and relational data modeling, data architecture, SQL, data warehousing, and data governance, with the ability to establish modeling standards and ensure data consistency, quality, and integrity across enterprise systems. Key Responsibilities Design and maintain conceptual, logical, and physical data models aligned with business requirements and enterprise data architecture standards. Translate complex business requirements into scalable and reusable data structures that support operational, analytical, and reporting needs. Develop relational, dimensional, and analytical data models, including star schemas, snowflake schemas, fact tables, dimension tables, and normalized data structures. Design data models for Data Warehouses, Data Marts, Data Lakes, and Lakehouse architectures. Perform detailed source system analysis and data profiling to understand data structures, relationships, dependencies, quality issues, and transformation requirements. Work closely with business stakeholders and subject matter experts to define business entities, attributes, relationships, hierarchies, and business rules. Collaborate with Data Architects and Data Engineers to convert logical models into optimized physical models suitable for target technology platforms. Define and maintain data dictionaries, metadata, naming conventions, business definitions, data relationships, and modeling documentation. Perform source-to-target data mapping and support ETL/ELT teams in accurately implementing business and transformation rules. Design models that support enterprise reporting, business intelligence, advanced analytics, and regulatory reporting requirements. Optimize data models for performance, scalability, maintainability, and efficient data consumption. Ensure data models comply with organizational data governance, security, privacy, data quality, and architecture standards. Identify data redundancies, inconsistencies, and structural gaps and recommend improvements to enterprise data structures. Conduct data model reviews and ensure consistency across applications, domains, and enterprise data platforms. Support Master Data Management (MDM) and reference data initiatives by defining consistent data entities, relationships, and standards. Maintain model versioning and manage changes resulting from evolving business requirements and source-system modifications. Collaborate with cross-functional teams, including Data Engineering, Data Architecture, BI, Analytics, Application Development, Data Governance, and Business teams throughout the data lifecycle. Support database and data warehouse design activities, including normalization, denormalization, indexing considerations, and data structure optimization. Participate in data migration and modernization programs by analyzing legacy data structures and defining appropriate target-state data models. Provide modeling guidance and best practices to technical teams and ensure adherence to established enterprise data modeling standards. Requirements 5+ years of experience in Data Modeling, Data Architecture, Data Engineering, Data Warehousing, or a related data discipline. Strong hands-on experience developing conceptual, logical, and physical data models. Strong knowledge of dimensional modeling, relational modeling, normalization, denormalization, star schema, and snowflake schema. Experience with enterprise data modeling tools such as ER/Studio, erwin Data Modeler, SAP PowerDesigner, or similar tools. Advanced knowledge of SQL and strong understanding of relational database concepts. Experience working with Data Warehouses, Data Lakes, Data Marts, and/or Lakehouse architectures. Good understanding of ETL/ELT processes, source-to-target mapping, data integration, and data transformation. Experience with major database and data platforms such as Oracle, SQL Server, PostgreSQL, Snowflake, Databricks, Azure Synapse, or similar technologies. Understanding of metadata management, data lineage, data quality, Master Data Management, and data governance concepts. Experience working in Agile delivery environments and collaborating with technical and business stakeholders. Strong analytical and problem-solving capabilities with the ability to understand complex data landscapes. Excellent stakeholder management, communication, and documentation skills. Previous experience within banking or financial services would be an advantage. Benefits PF Fuel Allowance Annual Leaves Annual Performance Based Bonus Annual Increment OPD IPD