Data Warehousing Specialist

Join a leading Financial Services firm in their quest for excellence Are you a skilled Data Warehousing Specialist seeking an exciting opportunity to make a significant impact? Our client, a prominent player in the financial industry, is actively seeking a talented professional like yourself to join their dynamic team. You will need to establish and lead a world class data analytics/warehouse capability for the company to enable future needs for advanced analytics and AI.

Maintain and support:

• Existing MIS databases.
• Existing reports and dashboards.
• Existing data warehouses.

Develop, test, deploy, maintain and support new databases, and reporting, data warehouse and business intelligence applications from high-level business requirements and designs, through the Software Development Life Cycle.

Remain informed about developments and trends in the data enablement field to assist the business to keep its data analytics and management capability up-to-date, and able to meet the future needs of the business in a constantly maturing and increasingly complex short-term insurance industry.

Outputs:

Internal Process:

• Collaborate with Project Managers and Business Leaders to deliver quality, effective management information, data warehouse and business intelligence applications, in line with the agreed development process and business needs.
• Collaborate with stakeholders to gather requirements, conduct analysis and prioritise requests.
• Conduct research and evaluate potential technical solutions to identified business problems.
• Translate business requirements into workable solutions and document solutions into technical specifications, partnering with Business and/or System Analysts when required.
• Design and code new database and analytics functionality using code that is readable, maintainable and reusable.
• Conduct Unit Testing of own code and resolve all issues/queries timeously.
• Contribute to user acceptance testing (UAT) to ensure that functionality is working correctly.
• Deliver solutions into the applicable production environment once testing has been completed.
• Provide stakeholders with regular feedback on the technical design and timelines for solution ensuring that business needs are met.
• Maintain existing databases and applications according to change requests approved by business as and when needed.
• Diagnose root causes of issues through problem-solving and recommend potential solutions.
• Monitor performance of solutions and make recommendations to improve the performance and functionality of the solutions, where appropriate.
• Log issues found in existing systems as internal change controls and ensure successful resolution of issues.

Responsibilities:

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 company short-term insurance business, in alignment with the companys standards and the South African financial services regulatory framework.

Self-management and Teamwork:

• Provide authoritative expertise and advice to colleagues.
• Develop and maintain productive and collaborative working relationships with peers and team members.
• Deliver on Service Level Agreements made with colleagues.
• Continuously develop own expertise in terms of industry and subject matter development and application thereof in an area of specialisation.
• Participate and contribute to a culture of work-centric thinking, productivity, service delivery and quality management.
• Contribute to continuous innovation through the development, sharing and implementation of new ideas and involvement of peers.
• Take ownership for driving career development.

Finance:

• Manage financial and other company resources under your control with due respect.

Competencies:

• Business Acumen.
• Client / Stakeholder Commitment.
• Drive for Results.
• Leads Change and Innovation.
• Motivating and Inspiring Team.
• Collaboration.
• Impact and Influence.
• Self-Awareness and Insight.
• Diversity and Inclusiveness.
• Growing Talent.

Skills:

• Communication articulating information and challenging ideas.
• Analysing and interpreting data.
• Problem-solving.
• Planning and organising time and task management.

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.
• On- the-job training/qualifications:
• Microsoft Sql Server.
• Oracle.
• Power BI.
• Advanced MS Excel.
• Starquest.

Some experience in predictive analytic platforms will be advantageous. These include:

• Python.
• Scala.
• Spark.
• AWS Sagemaker.

Some experience in Azure / AWS platform services will be advantageous. These include:

• Azure SQL elastic instance.
• Data factory.
• PowerBI.
• AWS RDS.

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 the data development industry.
• The candidate must have a 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.