Senior Business and Systems Analyst
Senior Analyst: Business and Systems Analysis | Johannesburg | Permanent
Lead complex analysis initiatives where business requirements, technology, systems modernisation and responsible AI come together. This is an opportunity to influence high-impact technology outcomes within a sophisticated, regulated environment.
The Senior Analyst will be deployed across Group Technology domains, programmes and squads, providing high-quality business and systems analysis for complex, cross-functional and strategically significant initiatives. The role covers the full analysis lifecycle, from elicitation and modelling through solution design, testing, adoption and traceability.
A distinctive part of the role is the use of AI-enabled tooling to recover requirements, business rules, process logic and data requirements from existing systems, particularly where documentation is incomplete or outdated. The successful candidate will combine deep analytical expertise with strong systems understanding, sound judgement and the ability to validate AI-generated insights against business and technical realities.
The organisation is a leading South African financial markets institution operating within a highly regulated environment. Its technology function supports critical market infrastructure and services, creating an environment where analytical quality, resilience, security, governance and innovation are central to successful delivery.
What You'll Do
Deliver analysis across complex, multi-team and cross-domain technology assignments.
Develop analysis plans, estimate effort, identify dependencies and manage delivery against agreed timelines.
Elicit, analyse, specify and validate business and system requirements through workshops, interviews, observation, documentation, systems and data analysis.
Produce business requirements, functional and non-functional requirements, process models, user stories and acceptance criteria.
Apply BPMN, UML, data modelling and interface specification techniques where appropriate.
Maintain traceability from business need through requirements, solution design and testing.
Conduct feasibility, cost and benefit analysis and contribute to business cases and option assessments.
Work closely with architects and engineers to ensure solution designs address business and system requirements.
Review test coverage, support user acceptance testing and participate in defect triage and root cause analysis.
Use AI-assisted tooling to analyse source code, configurations, message schemas, integration definitions and operational records.
Recover and validate business rules, process logic, data structures and interface behaviour from legacy systems.
Clearly distinguish confirmed requirements from AI-inferred behaviour and apply appropriate human verification.
Use AI to accelerate requirements drafting, summarisation, traceability, acceptance criteria and test scenario generation.
Contribute to modernisation and migration initiatives by establishing validated baseline requirements for existing systems.
Build effective relationships with business owners, product owners, engineering teams, architects, testers and other stakeholders.
Facilitate workshops, manage stakeholder expectations and influence scope and solution decisions through evidence-based analysis.
Participate in governance and design authority forums where required.
Contribute to the development of analysis standards, templates, reusable artefacts and Centre of Enablement practices.
Share knowledge, mentor less experienced Analysts and contribute to the analysis community of practice.
Identify opportunities to improve analysis practices, tooling and delivery efficiency, particularly through responsible AI adoption.
What You Bring
A Bachelor's degree in Computer Science, Information Technology, Information Systems, Engineering or a related discipline.
Business Analysis certification from a recognised institution, such as IIBA CBAP or an equivalent qualification.
At least 10 years' experience in Business Analysis, Systems Analysis or an equivalent analysis role.
At least 3 years' experience working on complex, multi-team or cross-domain initiatives.
Experience delivering analysis across multiple business or technology domains, or within a shared services or consulting environment.
Experience analysing existing systems for modernisation, migration or replacement, including recovering requirements where documentation is incomplete or outdated.
Demonstrated practical experience using AI-assisted tooling in analysis work.
Advanced requirements elicitation, analysis, specification and validation capability.
Strong business process modelling and systems analysis skills, including BPMN, UML, data modelling and interface specification.
Strong understanding of Agile analysis practices, including user stories, acceptance criteria, backlog refinement and definitions of ready and done.
Sound understanding of the software development lifecycle from design and build through testing, release and operational support.
Ability to interpret data to support requirements, impact assessments and decision-making.
Experience with tools such as Jira, Confluence, Azure DevOps and relevant modelling tools.
Strong facilitation, negotiation, communication and stakeholder management skills.
Ability to adapt quickly to different domains, teams, assignments and ways of working.
Understanding of information security, POPIA, intellectual property and audit considerations relevant to analysis and AI tooling.
Financial services, capital markets or regulated-environment experience is strongly preferred.
An Honours or postgraduate qualification is advantageous.
Agile analysis certification such as IIBA-AAC, PSPO or SAFe is advantageous.
Training or certification in AI tooling for analysis or software engineering is advantageous.
What Success Looks Like
Analysis outputs are complete, accurate, traceable and delivered within agreed timelines.
Stakeholders have a clear understanding of requirements, options, dependencies, risks and trade-offs.
Requirements remain traceable from business need through solution design and testing.
Legacy systems are effectively analysed and their business rules and requirements recovered where documentation is limited.
AI-assisted analysis improves efficiency without compromising quality, confidentiality, governance or professional judgement.
AI-generated findings are appropriately validated and clearly distinguished from confirmed requirements.
Solutions align with business needs, technology standards, regulatory obligations and longer-term strategic objectives.
Stakeholder relationships support effective collaboration across business, architecture, engineering, testing and other technology functions.
Reusable analysis practices, knowledge and artefacts strengthen the broader Analysis and Design Centre of Enablement.
Continuous improvement initiatives deliver measurable improvements in analysis quality, efficiency or cycle time.