Data Modeller-1 at FNB South Africa

Are you someone who can

• Execute on data modelling standards, principles, frameworks and tools
• Coordinate and prioritise the data modelling work within the Business area
• Involved in the entire data modelling lifecycle i.e. Logical to Implemented Physical Model and Semantic Model
• Understand the reference and master data requirements and co-ordinate the use of surrogate keys and enterprise code values when building out data products with relevant stakeholders
• Provide input into key metrics related to measuring the progress with respect to data modelling
• Optimise and update logical and physical data models to support new and existing projects for Business area
• Ensure that the source to target mapping is done in accordance to the requirement
• Maintain all extract, transform, load (ETL) and business rules within the data model
• Maintain all model related metadata
• Recommend opportunities for reuse of data models in new environments
• Review modifications to existing data modeling software to improve efficiency and performance
• Evaluate data models and physical databases for variances and discrepancies
• Ensure modelling standards and principles are always adhered to
• Develop modelling standards and principles as needed

You will be an ideal candidate if you have experience in

• Knowledge of logical data modelling, and use of industry data models (e.g.IBM, Teradata, etc.).
• Understanding of the Inmon methodology
• Experience working in data warehousing environment with good understanding of data ingestion, enterprise alignment (ETL) and design based on consumption requirements
• Knowledge of dimensional data modelling using Kimball methodology
• Experience using data modelling technologies such as Erwin.
• Developing data models in a banking environment.
• Understanding and experience in implementing data management domains and technologies (e.g. data modelling, metadata management, data quality and profiling, information architecture, etc.).
• Experience in networking and team collaboration, communication, and presentation.

Experience

• 4-5 years experience in a data environment with hands-on relational, dimensional, and/or analytic experience (using relational database management systems (RDBMS), dimensional, NoSQL data platform technologies, and extract, transform, load (ETL) and data ingestion protocols).
• Experience with data warehouse, data lake, lake house and enterprise big data platforms in multi-data-center contexts required

End Date: July 24, 2025