Locations: Centurion l Johannesburg l Cape Town Working model: Hybrid Specification: The Data Engineer will have for data analysis, data manipulation, and data modelling. The candidate will be responsible for understanding Experience in data mining, large scale data modelling and business requirements gathering/analysis. Experience implementing data modelling methodologies like Dimensional Modelling and / or Data Vault. Working information to discover trends and patterns. Data Modelling (Relational and Star Schema). Database design
Locations: Centurion l Johannesburg l Cape Town Working model: Hybrid Specification: The Data Engineer will have for data analysis, data manipulation, and data modelling. The candidate will be responsible for understanding Experience in data mining, large scale data modelling and business requirements gathering/analysis. Experience implementing data modelling methodologies like Dimensional Modelling and / or Data Vault. Working information to discover trends and patterns. Data Modelling (Relational and Star Schema). Database design
structured and unstructured data sets. Responsibilities: Model complex business problems, discovering insights intelligent automation and predictive modelling. Build machine learning models from and utilises distributed Kafka. Provide input into Data management and modelling infrastructure requirements and adhere to the Ensure business integration through integrating model outputs into end-point production systems, are understood Measure proficiency in using the diagramming and modelling techniques vital for requirements analyses. Qualifications
vulnerabilities. Develop and maintain fraud detection models that are both accurate and minimize disruptions Optimizing Detection Models: Continuously review, analyze, and improve core models used to detect fraud legitimate transactions. This involves adjusting models and thresholds based on factors like desired alert Integrate new data sources when needed to improve model effectiveness. Assist data engineering efforts to data analysis. Experience applying statistical modelling techniques to solve complex problems. Familiarity
vulnerabilities. Develop and maintain fraud detection models that are both accurate and minimize disruptions Optimizing Detection Models: Continuously review, analyze, and improve core models used to detect fraud legitimate transactions. This involves adjusting models and thresholds based on factors like desired alert Integrate new data sources when needed to improve model effectiveness. Assist data engineering efforts to data analysis. Experience applying statistical modelling techniques to solve complex problems. Familiarity
Hana environment. Design and develop SAP BW data models and Data Flows Implement and maintain data security Years SAP BW experience 3 Years SAP Analytics Cloud model experience Knowledge and experience of SAP Hana
Development Life Cycle models (Waterfall, Rapid Application Development, Spiral Model, Agile, etc.) required
reporting
TypeScript, etc.
Comfortable with data modelling, Qlik NPrinting, data mapping, back and front-end
existing Qlikview models.
Data Clean up from source.
Developing new Qlikview models.
Maintaining
CSS, C#, TypeScript, etc. Comfortable with data modelling, Qlik NPrinting, data mapping, back and front-end existing Qlikview models. Data Clean up from source. Developing new Qlikview models. Maintaining automation