Lead Assistant 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

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.