Intermediate Data Modeler

SUMMARY:
The Role:

A Top Bank is searching for an Intermediate level Data Modeller with experience in dimensional modelling techniques and knowledgeable in Agile, Banking Products and DevOps Tools.

Essential Experience:

• 3yrs IT related experience and 2yrs+ in a Data Modelling experience
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POSITION INFO:
The Role:

A Top Bank is searching for an Intermediate level Data Modeller with experience in dimensional modelling techniques and knowledgeable in Agile, Banking Products and DevOps Tools.

Skills and Experience:

Essential Experience:

• 3yrs IT related experience and 2yrs+ in a Data Modelling experience
• Intermediate Level using SQL in Databases
• Practical experience in relational and dimensional modelling techniques as well as leading teams of data modeler
• Knowledgeable and experienced in Agile Concepts, Banking Product and DevOps Tooling and methodologies

 

Essential Qualification:

• BSc (Hons): Computer Science
• BSc (Hons): Information Systems
Key Accountabilities:

KPAâ??s:

• Practical experience in relational and dimensional modelling techniques as well as leading teams of data modelers
• Developing custom data models as well as data modelling utilising Industry data models such as IFW BFMDW Experience in model management
• Compiling and monitoring standards and developing/maturing a data modelling practice OO modelling experience also an advantage
• Experience using Infosphere Data Architect or any other Data Modelling Tool Firm
• Understanding of Data Management (DMBOK), systems development lifecycle methodologies and IT Architecture Relevant regulatory knowledge, and understanding of banking and financial services
• Experience in NOSQL and other forms of database modelling advantageous

 

Personality and Attributes:

Characteristic Traits:

• Detail orientated
• Focused and self driven
• Problem solver and ability to think out of the box
• Analytical and ability to grasp new technologies quickly
• Innovative
Other:

Skill Levels:

Advance Level on:

• Language skills
• Data analysis and inference
• Data Integrity and Data Modelling
• Data Warehouse Layers
• Metadata
• Data Quality
• Data Warehousing Overview and Architecture
• Database Model Concepts
• Data and business requirements gathering
• Data Modelling Tools
• Industry Model Understanding
• Pattern Recognition, conceptual and abstract thinking
• Presenting
• Problem solving and creativity

 

Basic Level:

• Data Governance
• Data Architecture Management
• Data Integration
• Master and Reference Data Management




 

NB! This job is now closed. You can apply for other jobs by uploading your CV.




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