Job Description

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

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