Data Modeler
Dicetek LLC
Date: 1 day ago
City: Dubai
Contract type: Contractor
We are seeking a highly skilled Enterprise Data Modeler to design, develop, and maintain enterprise-level data models that support our banking operations, analytics, and regulatory compliance. The ideal candidate will have a deep understanding of financial services data structures, a strong grasp of data governance principles, and experience working in complex, regulated environments.
Key Responsibilities
Key Responsibilities
- Design and maintain conceptual, logical, and physical data models across banking domains (e.g., Retail, Corporate, Risk, Compliance).
- Collaborate with business and IT teams to gather requirements and translate them into scalable and compliant data models.
- Ensure data models support regulatory requirements (e.g., BCBS 239, AML, KYC, Basel III) and internal data governance policies.
- Work closely with data architects, engineers, and analysts to implement models in data warehouses, data lakes, and operational systems.
- Drive standardization of data definitions and data quality metrics across the enterprise.
- Support data lineage, metadata management, and data cataloguing initiatives to enhance data transparency and traceability.
- Develop and maintain documentation of models, data dictionaries, and data flows.
- Assist in M&A data integration and system consolidation projects.
- Stay current with industry trends, data modelling tools, and regulatory changes affecting data structures.
- Bachelor’s or master’s degree in computer science, Information Systems, Data Science, or a related field.
- 5+ years of experience in data modelling, ideally within banking or financial services.
- Expertise in data modelling tools such as ERwin, IBM Infosphere Data Architect, or similar.
- Strong understanding of relational, dimensional, and data vault modelling techniques.
- Experience working with data warehouse architectures, data lakes, and cloud-based platforms (Azure).
- Solid knowledge of banking systems and data domains (e.g., customer, account, transaction, product, risk, compliance).
- Familiarity with data governance frameworks and regulatory compliance requirements (e.g., BCBS 239, GDPR).
- Strong SQL skills and understanding of database platforms (Oracle, SQL Server, Postgress, DB2).
- Datawarehouse design methodologies understanding.
- Experience with master data management (MDM) and metadata management tools.
- Knowledge of real-time data modelling for payments and fraud detection.
- Exposure to big data technologies (e.g., Hadoop, Spark) and streaming platforms (Confluent).
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