Data Modeler

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

Work arrangement
Yes