The Data Warehouse Manager must also establish and lead a world class data analytics/warehouse capability to enable future needs for advanced analytics and AI. Role-specific Responsibilities and Outputs Develop, implement and document Business Intelligence Solutions (Internal Process): Contribute to the overall data warehouse architecture and data base designs Maintain and oversee the administration and maintenance of the data warehouse Develop and maintain Business Intelligence and reporting technologies and processes Translate stakeholder requirements into technical specifications for Business Intelligence (BI) reports and applications Design and develop reports and dashboards based on Business Requirements Document (BRD) and customer specifications Develop feasible technical specifications and process flows for data provision activities in support of the development of business intelligence solutions Ensure the continued maintenance and enhancement to existing business intelligence solutions Within user specifications extract, transform and load (ELT) data using the relevant tools Verify and quality assure of data provided Provide support to business intelligence users on data-related issues Future development and planning Conduct research and undergo training where appropriate, in order to remain abreast of data enablement trends and understand their application in the short-term insurance industry Assist management and colleagues to make the right decisions in terms of planning future data enablement infrastructure, architecture and applications in the Momentum short-term insurance business, in alignment with Momentum Metropolitan group standards and the South African financial services regulatory framework. Experience and Qualifications Relevant IT and data analytics qualifications e.g. B.Tech or B.Sc. (Informatics) - Essential Dimensional modelling and/or relevant Microsoft certification Advantageous 3 5 years of management experience taking care of teams between 5 8 people - Essential Minimum Experience Methodologies The candidate must have ability to elicit data requirements from stakeholders The candidate must have clear documentation skills Principles The candidate must be familiar with design patterns in data development industry. The candidate must have solid understanding of Metadata constructs. The candidate must have clear understanding of EDW Knowledge of Domain driven design would be an advantage The candidate must be familiar with the concept of Data Marts The candidate must be familiar with abstraction techniques Modelling The candidate must have proven data modelling techniques (3 years) The candidate must have knowledge and experience in Ralph Kimball data warehouse modelling (3 years) Knowledge of Immon data warehouse modelling techniques would add an advantage The candidate must have data normalization skills most especially the 2nd Normal form Data Transportation The candidate must have solid experience of ETL systems The candidate must have solid experience of sourcing, staging and loading The candidate must be familiar with parallel loading principles The candidate must be familiar with source to target mapping Development Software The candidate must have advanced knowledge of T-SQL (4 years) and the following concepts Dynamic T-SQL Multi-threading Performance optimisation and tuning The candidate must have practical experience of SQL Server Database Engine (4 years) The candidate must have practical experience of MS SSIS ETL software (4 years) The candidate must have practical experience of MS SSAS OLAP software (4 years) The candidate must have practical experience of MS Visual Studio Data Tools (4 years) Knowledge of Database Administration would add an advantage Expert knowledge in configuration of database hardware resources Repository type The candidate must be able to source data from different repositories The candidate must be fully acquainted with Microsoft SQL Server repository Knowledge of Data Lake would be an advantage Knowledge of Oracle would be an advantage Knowledge of Hadoop is not essential but will also be an advantage
