Chief Data Officer

Description

This function is accountable for business ownership of Project Olympus’s Data Strategy which encompasses Data capabilities, the Data operating model (centralized and decentralized function), Analytics capabilities, and driving the data culture across the bank. The incumbent will be responsible for the creation, interpretation, and implementation of the data strategy, including responsibility for all technologies build, automation, processes, and personnel which are required to deliver the Data portfolio across all servicing propositions. The Head of the Data Chapter and Analytics Chapter will report into the CDO to deliver a data driven banking service to Project Olympus’s customers.

At its core, the CDO is an individual who possesses a unique blend of technical expertise, strategic thinking, and business acumen. They act as a bridge between data teams, stakeholders, and end-users, translating complex data concepts into actionable insights that drive value and innovation.
With their deep understanding of data technologies, market trends, and user needs, the CDO play a crucial role in shaping the strategic direction of data products. They analyse market demands, identify opportunities, and make data-driven decisions to drive product innovation and meet customer expectations.
The incumbent will be individually accountable for achieving results through the Data Chapter and Analytics Chapter and collaboration with other Product Owners and Chapter Leads within the CTO-Organisation and the broader OML Group.

KEY RESULT AREAS

Project Olympus aims to set a differentiated standard for its Data Capabilities. This includes:

The CDO is responsible for the development and implementation of Project Olympus data strategy and framework that will ensure that Project Olympus as an enterprise is able to leverage data assets in the quest to commercializing the assets and managing the associated risks with the assets. To lead the Data journey in Project Olympus by supporting various Business unit in the use of data capabilities to support the build of data products (real time or non-real time) and deployment thereafter to where needed. To lead and support the definition, development, implementation, continuous improvement, communication and related monitoring/administration of policies, processes, standards, and guidelines that pertain to data governance. Engaging with business stakeholders to understand their business needs. Establishing a strong data-driven approach to decision making across the organization Design and build of data architecture, infrastructure, and operations. Overseeing data management, data analytics, and data governance Ensure that there are controls to manage Partner data management. Ensure that the overall Bank’s data ecosystem fits into Enterprise Data Architecture standards. Ensure data governance is done upfront (as possible) in any design, so that Master and ref data management issues are avoided. Ensure different Data technologies and storages (e.g. Event Hub, Stream Processing, Data Platform, Data Science Platform, DynamoDB) integration into the Enterprise Architecture enables flexibility and adaptability. Incorporate AI, automation, and machine learning capabilities and produce operating model of how do build, train, and deploy models quickly, and wherever needed easily. To lead the strategy and execution of the data quality management practice ensuring a high quality of data (i.e. completeness, conformance, and accuracy of enterprise data) and managing all elements affecting this. Work within an , collaborating with to deliver value incrementally. They participate in sprint planning and backlog grooming, prioritizing data-related tasks based on business value. To lead the development and build of data and analytics capabilities that will enable data lifecycle management practice that will create and ensure compliance with the data standards for Project Olympus and informing the enterprise data architecture functions. To ensure there is documentation and training material of what data and analytics capabilities are, what they do, and why they are needed. It is also required that these a continuously communicated and shared to the broader Olympus programme to encourage the adoption of data and build Olympus’s data culture. Support PO’s and be an evangelist in driving the use of data in Olympus. Drives a central Data governance function that creates data standards and provides data governance capabilities that supports the Data Chapter in its execution of adherence data standards. Measure and report on Data chapter and Analytics chapter standards adherence to provide a view back to the Project Olympus’s risk function on Data Policy risk appetite. Ensure the different Skillset swim lanes in each Quality gate of the data product lifecycle and Analytics product life cycle has standards established and measured. Proactively map data risks and ensure compliance with data related regulations, policies, and standards Drive a finops function across data capabilities build and use to ensure there isn’t wasteful expenditure and drives cost effective use of data. Develop and maintain a framework to forecast data costs for budgets Accountable for Servicing Technology Spend and Investment stack (TCO) Including monitoring, tracking and reporting on Tech Stack performance and ensuring resolution where requiredAccountable for Incident Management and Change SlotsManagement of SLA with Technology Platforms and Enablement Owns the backlog for Workflow and Automation Facilitates demand with Product and determines impact for the Servicing business.Facilitates the relationship /engagement with Servicing.

Ensure cost efficiency through financial and corporate governance

Contribute to the development and implementation of fit for purpose budgets. Manage supplier relationships, and budgets associated with projects.

Manage quality people practices

Align own behaviour with the organisation culture and values. Share and transfer product, process and systems knowledge to colleagues and team members. Collaborate and work with the business to deliver required service levels. Actively share information with other team members regarding successes, issues, trends and ideas.

Leadership Effectiveness

Role model client centric behaviour and demonstrates Management & Leadership Effectiveness Align others to best practice and set standards of excellence. Define performance parameters and measurements for area under supervision Manage performance and service delivery through direct reports and their teams. Oversee selection, performance management and talent management in business area. Ensure effective talent management including succession planning; transformation per the BBBEE targets of the segment and national EAC (economically active population), skills development and training for a sustainable operating model and diverse high performing team Enable a culture of continuous learning and development in the organisation. Drive and support change and culture shift initiatives Ensure that the business unit is compliant with Group Governance Framework, Segment strategy and operating model and any statutory legislation and regulations Data Product Owner needs to understand the business context in which they work. This includes understanding the organization’s goals, objectives, industry landscape, and market trends.

ROLE REQUIREMENTS

Qualifications:

Preferred Post graduate Computer Science or Engineering degree

Proven experience in:

Minimum of 8 - 10 Years in a relevant Senior Management role (Data and Analytics) - Advantageous AWS Data Technologies such as Data Catalogue tooling, Data Quality tooling, DBT, Data Lakehouse, Data Warehouse (Snowflake/Redshift/etc) Data Science Technologies e.g. Predictive Analytics, and Machine Learning. Building a modern data tech stack Stream Technologies such as Kafka and Flink Solid understanding of master and ref data architecture Able to engage and influence at a senior level.

Skills

Education

Closing Date

11 June 2024

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