Responsible for building the organisations data collection systems and processing pipelines. Oversee infrastructure, tools and frameworks used to support the delivery of end-to-end solutions to business problems through high performing data infrastructure.
Responsible for expanding and optimising the organisations data and data pipeline architecture, whilst optimising data flow and collection to ultimately support data initiatives.
Key Responsibilities / Accountabilities Data :
Owns and extends the business’s data pipeline through the collection, storage, processing, and transformation of large data-sets and oversee the process for creating and maintaining optimal data pipeline architecture and creating databases optimized for performance, implementing schema changes, and maintaining data architecture standards across the required Standard Bank databases.
Oversee the assembly of large, complex data sets that meet functional / non-functional business requirements and align data architecture with business requirements.
Responsible overseeing the process for enabling and running data migrations across different databases and different servers and defines and implements data stores based on system requirements and consumer requirements.
Oversee, design, and develop algorithms for real-time data processing within the business and to create the frameworks that enable quick and Product :
Build analytics tools that utilise the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
Create data tools for analytics and data scientist team members that assist them in building and optimising Standard Bank into an innovative industry leader.
Monitor the existing metrics, analyse data, and lead partnership with other Data and Analytics teams in an effort to identify and implement system and process improvements.
Utilise data to discover tasks that can be automated and identify, design, and implement internal process improvements : automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Developing ETL processes that convert data into formats for consumption. Risk, Regulatory, Prudential and Compliance :
Responsible for executing testing and validation in line with data governance and quality business requirements. People :
Liaise with and collaborate with data analysts, data warehousing engineers, and data scientists in finding and applying best practices within the Data and Analytics department as well as defining the business’s data requirements, which will ensure that the collected data is of a high quality and optimal for use across the department and the business at large.
Acts as a subject matter expert from a data perspective and provides input into all decisions relating to data engineering and the use thereof.
Provide guidance in terms of setting governance standards. Strategy :
Responsibility for contributing to the continual improvement of the business’s data platforms through thorough observations and well-researched knowledge.
Keeps track of industry best practices and trends and through acquired knowledge, takes advantage of process and system improvement opportunities.
Provide oversights and expertise to the Data Insights and Analytics that is responsible for the design, deployment, and maintenance of the business’s data requirements.
Preferred Qualification and Experience Minimum qualification 1 Post Graduate Degree : Information Technology Minimum qualification 2 Post Graduate Degree : Information Studies Preferred qualification 1 Masters Degree : Information Technology Preferred qualification 2 Masters Degree : Information Studies Knowledge / Technical Skills / Expertise IT Architecture :
Architectural methodologies used in the design and development of IT systems. Data Integrity :
The ability to ensure the accuracy and consistency of data for the duration that the data is stored as well as preventing unintentional alterations or loss of data. IT Applications :
Knowledge and understanding of IT applications and architecture. Data Analysis :
Ability to analyse statistics and other data, interpret and evaluate results, and create reports and presentations for use by others. Knowledge Classification :
The ability to apply metadata to information to make it easy for other people to find.