An AWS Data Engineer with -12 years hands-on data engineering experience is required to join a team of Business Intelligence (BI) Experience Technical data modelling and schema design (“not drag and drop”) Kafka
solutions. Designing and implementing predictive models to optimize customer segmentation, credit risk analysis and machine learning algorithms, with hands-on experience applying them to real-world problems
solutions. Designing and implementing predictive models to optimize customer segmentation, credit risk analysis and machine learning algorithms, with hands-on experience applying them to real-world problems
offers a unique blend of strategic leadership and hands-on technical expertise, aimed at safeguarding our availability of our systems and data. This hybrid working model provides the flexibility to balance your professional
Reporting) Support
advantage. • Must have a minimum of 2 years of hands-on experience in MS Cloud-based technologies, such • Understanding of the following architecture models: Client/Server (LAN/WAN), Service-Oriented Architecture Micros/Simphony/Opera POS systems would be advantage. • Hands-on knowledge of IT Automation/Scripting for information
advantage. • Must have a minimum of 2 years of hands-on experience in MS Cloud-based technologies, such • Understanding of the following architecture models: Client/Server (LAN/WAN), Service-Oriented Architecture Micros/Simphony/Opera POS systems would be advantage. • Hands-on knowledge of IT Automation/Scripting for information
creating data flow diagrams (DFDs), defining data models, ensuring data lineage, and implementing data governance development with a focus on data lineage, data modeling, and data flow design. Proven experience with in creating data flow diagrams (DFDs) and data models.
he Data and BI Analyst will be assisting the modelling and analytics team with all analytics, reporting business on key business metrics and assist the modelling team to drive strategic decision-making and better enable quantitative analysis for statistical and modelling team. Explore data to understand its structure trends, and correlations. Design and build data models, dashboards, and reports using business intelligence
the development and implementation of actuarial models, and collaborating with cross-functional teams regulatory requirements. Modelling and Coding: Develop and maintain actuarial models to analyse and forecast skills to enhance efficiency and accuracy in modelling processes. IFRS17 Reporting: Assist in the implementation consistency and accuracy of data used in actuarial models and financial reporting. Identify and resolve discrepancies opportunities for automation in data processing, modelling and reporting. Requirements: Bachelor's degree