About this role
Core strengths / capabilities
• Requirements & analysis: discovery workshops, user stories, epics, acceptance criteria, NFRs, prioritization support • Process & operational design: as-is/to-be, Visio, service blueprints, controls and handoffs • Data & integration awareness: data lineage, field mapping, event flows, basic SQL (where relevant) • Delivery support: backlog refinement, sprint support, UAT planning/execution, triage, defect management • Stakeholder management: influencing across Product, Tech, Ops, Compliance/Risk; clear written comms • Quality & governance: traceability, change impact assessment, RAID management, documentation discipline
ypical deliverables
• Problem statement, scope, assumptions, success measures • Epics/features, user stories, acceptance criteria • Process maps (as-is/to-be), customer journeys • Data dictionary, mapping specs, interface requirements • UAT approach, test scenarios, sign-off pack
Tools/ways of working (examples)
Jira/Confluence, Visio, Excel, SQL (basic–intermediate), Agile/Scrum/Kanban.
Nice “differentiators” (optional)
• Experience in regulated environments (risk, audit, controls-by-design) • Familiarity with cloud patterns, microservices, event-driven architecture (high-level) • Ability to simplify complex stakeholder needs into an MVP and phased roadmap
Graduate in Computer Science, Data Science, or related field. 3-4 years of experience in data engineering or a related field.