Data Modeler

شرح موقعیت

Core Skill Requirements Teradata Data Modeling (Expert Level) 10+ years of experience in Teradata Data Warehousing and Data Modeling Strong expertise in Logical & Physical Data Modeling Experience in enterprise-scale data warehouse implementations Expertise in dimensional and normalized modeling techniques Strong understanding of data governance, metadata, and data quality Ability to translate business requirements into scalable data models CLDM (Communications Logical Data Model) – Expert Level Deep expertise in CLDM implementation within banking environments Strong knowledge of banking domains including Customer, Billing, Product, Network, Usage, and CRM Experience customizing CLDM and mapping banking source systems into CLDM structures Strong understanding of banking enterprise data integration standards FSDM (Financial Services Data Model) – Deep Knowledge Strong hands-on experience with FSDM implementation Deep understanding of banking and financial services domains including Accounts, Loans, Payments, Risk, Compliance, and Regulatory Reporting Experience designing enterprise financial data models aligned with FSDM standards Strong knowledge of financial data governance, integration, and reporting requirements Logical Data Modeling Strong expertise in conceptual, logical, and physical data modeling Experience in ER modeling, normalization, and enterprise information architecture Hands-on experience with modeling tools such as ERwin Ability to define data standards, naming conventions, and governance practices Experience Requirements Banking Domain Strong banking industry experience preferred Knowledge of banking KPIs, subscriber lifecycle, and usage analytics Experience with banking operational and analytical systems Financial Services Domain Strong banking and financial services experience preferred Understanding of enterprise banking systems and regulatory requirements Experience supporting compliance, analytics, and financial reporting initiatives Data Governance & Quality Experience in data governance and data quality frameworks Strong understanding of data lineage, metadata management, and compliance standards