Manager

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 Typical 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. 4-6 years of experience in data engineering or related field.