BI Data Modeller

The primary technology used is IDA (Infosphere Data Architect (Data Modelling Tool)) and Aginity Workbench DB2.

It will also be most beneficial to have knowledge of IGC (Infosphere Governance Catalogue).

**Duties**:

- Design data models that meet the business requirements and align to the agreed architecture framework.
- 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
- Adopt the Enterprise Data Model (which is based on the IFW) as a standard for data model designs to leverage best practice and fast track data modelling efforts.
- Translate business requirements into data requirements.
- Analyse and profile the source data to understand data quality issues, relationships, patterns and rules in the data.
- Structure data requirements into logical data constructs based on the Enterprise Data Model, including ERD models, dimensional models to ensure optimal implementation.
- Compile Source to Target Mapping Specifications including the appropriate Transformation Rules
- Identifying definitive or authoritative source of data; analysing source data; and identifying gaps to target structures
- Enable physical implementation of the data structure by generating the first cut physical data model from the logical data model.
- Facilitate dataflow understanding by collating dataflow diagrams outlining the flow of data across systems and interfaces.
- Reduce non-value adding work by identifying opportunity for re-use of the Enterprise Data Model
- Maintain up to date knowledge of latest developments in the Data Modelling domain, including reading; continuous professional development courses; seminars and conferences.
- Assists to provide a comprehensive governed framework by working with the data modelling CoE and contributing towards defining the data modelling standards.
- Ensure consistency and re-use of data models by acting as a primary advocate of date modelling activities and methodologies and by driving the adoption of enterprise data modelling across the bank.
- Ensure improved performance by providing feedback on improvements to the data modelling framework.
- Perform review on work performed by team members as well as review and govern work performed by other modelling teams
- Identify opportunities to improve or enhance processes.
- Provide Overall Data Management Guidance and alignment to the Data Management framework and standards
- Seek opportunities to improve business processes, models and systems though agile thinking.
- Support the achievement of the business strategy, objectives and values
- Participate and support corporate responsibility initiatives for the achievement of business strategy

Skills & Experience Required:

- 5 - 8 years IT related experience with 5yrs+ in a Data Modelling role
- Able to demonstrate practical experience in relational and dimensional modelling techniques as well as leading teams of data modellers
- Experience using Infosphere Data Architect or any other Data Modelling Tool
- Has demonstratable experience in developing custom data models as well as data modelling utilising Industry data models such as IFW BFMDW
- Experience in model management
- Experience in 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

Advanced knowledge of:

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

Intermediate knowledge of:

- Using SQL in Databases
- Agile Concepts
- Banking Product Knowledge

Basic knowledge of:

- Data Governance
- Data Architecture Management
- Data Integration
- DevOps Tooling and methodologies
- Master and Reference Data Management

Qualifications/ Certification:

- Advanced Diplomas/National 1st Degrees/equivalent NQF level 6 qualification
- Bachelor of Commerce, Bachelor of Science: Information Systems / Computer Science Honours level
- TOGAF, DAMA