Data Modeller

R37 000 to R41 000 ctc pm

Client is a financial institution (bank) based in Midrand

Job Description In collaboration with the business and IT; design and maintain data models, dataflow diagrams, and metadata deliverables at both an enterprise and system / application level, to fulfil the business and architectural objectives for the organisation.
Job Requirements MINIMUM EDUCATION
• BSc Computer Science / Information Systems
• Or BTech in Information Technology
PREFERRED MINIMUM EDUCATION
• BSc Computer Science / Information Systems
MINIMUM EXPERIENCE
• 5 years plus and/or relevant industry experience as well as experience in the Data Modelling discipline.
• Able to demonstrate practical experience as a data modeller in a data modelling project.
• A good understanding of data and information management practise; a firm understanding of DMBOK would be advantageous.
• Understanding of banking and financial services
• Experience in creating conceptual, logical and physical data model.
• Hands on experience in using data modelling tool sets..
• Experience working with RDBMS platforms (e.g. SQL Server, Oracle, Netezza, Teradata, DB2)
• Knowledge of technical and business metadata
PREFERRED MINIMUM EXPERIENCE
• 5 years
CRITICAL COMPETENCIES
• Data analysis, Business Analysis
• Data Modelling, Dataflow design, Data Base Design
• Metadata
• Data Quality
• SQL
ADDITIONAL COMPETENCIES
• Communication skills (verbal and written)
• Self-motivated and a person who takes initiative without requiring constant instruction and guidance
• Deadline driven
• Presentation skills (MS PowerPoint essential)
• Attention to detail
• MS Office skills
• Report writing skills
• Presentation skills
• Collaboration skills
• Innovative
• Project management skills
ROLE & RESPONSIBILITIES
• Comply with Bank’s Data modelling Standards in all data modelling efforts.
• Design data models that meet the business requirements and align to the agreed architecture framework.
• Design required dataflow diagrams
• Design and collate dataflow diagrams outlining the flow of data across systems and interfaces.
• Liaise with SMEs, Data Stewards, IT and other stakeholders to design and collate dataflow diagrams.
• Liaise with SMEs, Data Stewards, IT and other stakeholders to design and collate data models.
• Ensure data modelling deliverables are delivered according to project plan and budget to meet commitment to stakeholders.
• Ensure all data modelling activities and deliverables are aligned to the development methodology and to the data modelling principles and standards
• Use data modelling tools to fulfil data modelling deliverables.
• Translate business requirements into data modelling requirements.
• Utilise Data profiling reports produced by Data Quality professionals, to gather information about data that needs to be modelled.
• Liaise with SMEs to define source to target mappings.
• Identify definitive or authoritative source of data; analysing source data; and identifying gaps to target structures.
• Identify opportunities to improve or enhance processes.
• Document required data lineage for identified data.
• Create or define metadata for systems, processes and data models.
• Define, review and ratify Enterprise Data Standards
KEY RESULT AREAS
Treating Customers Fairly and Compliance
• Create and maintain productive relationships with internal and external clients by providing advice and assistance
• Create understanding of the ‘real’ versus ‘perceived’ need through experience and expertise while complying with company policies, legislation and regulations
• Keep the client informed about progress through written communication, telephone communications, and/or face-to-face meetings
• Build a positive image by exceeding client expectations at all times
• Treat internal and external customers fairly at all times
Data Modelling
• Develop data models and data flows according to company standards
• Perform reverse engineering of physical data models from databases and SQL scripts.
• Maintain conceptual, logical and physical data models along with corresponding metadata.
• Familiarity with modelling tools that are currently in place within organizations