Description

Job Description

The Senior Business Analyst serves as the principal interface between business stakeholders, product owners, and delivery teams in the design, delivery, and continuous improvement of trade systems across the trade ecosystem. The portfolio spans Customs Risk Management and Trade Single Window solutions as well as Port and Cargo Community Systems, trade portals, regulatory and cross-border platforms, and the wider set of systems serving trade and supply-chain operations. The role combines product ownership, business process analysis, and systems thinking, applied across this portfolio and its operational and regulatory interactions.

Responsibilities

1.Act as the principal interface between clients, stakeholders, and the development team, fostering alignment, transparency, and a unified understanding of solution goals throughout the project lifecycle.

2.Lead the elicitation and analysis of business and functional requirements across the trade-systems portfolio -including Single Window, Customs Risk Management, Port and Cargo Community Systems, and other trade and cross-border platforms, and including requirements that arise from AI-driven use cases and their associated data needs -translating stakeholder input into clear, actionable specifications.

3.Lead the preparation of Business Requirements Documents (BRDs), Functional Requirements Specifications (FRSs), None Functional Requirements (NFRs) and User Story Specifications -whether authored directly or generated through AI skills and then critically reviewed, corrected, and owned by the analyst -ensuring deliverables are comprehensive, traceable, and compliant with established governance and quality standards.

4.Model and analyze business processes using industry-recognized standards such as BPMN and UML, developing clear AS-IS and TO-BE representations to support system design and process re-engineering.

5.Operate fluently across both the conventional, analyst-led business analysis process and the AI-native, skill-orchestrated operating model, selecting -demand by demand -whether conventional analysis, AI-assisted generation, or a blend of the two best fits the work in hand.

6.Classify incoming demand through typed intake -distinguishing business needs, change requests, general demand, incidents, procurement, and regulatory triggers -and produce a structured, uniquely identified intake record that correctly routes and anchors all downstream activity.

7.Orchestrate and supervise AI skills across intake, strategy and analysis, and BRD / specification generation: supply high-quality context, then critically review, correct, and take ownership of the generated output, proportioning the depth of human oversight to the maturity of each skill (heavier scrutiny for early-stage skills, lighter touch for production-grade ones).

8.Act as the human validation gate that AI cannot replace -securing stakeholder and product-owner sign-off and ensuring that no requirement enters the backlog without a typed, traceable demand behind it.

9.Act as Product Owner or proxy Product Owner, working with cross-functional teams and product managers to refine and maintain the product backlog, prioritize features, and ensure alignment with strategic objectives and delivery milestones.

Technical and Methodological Competencies:

• Practical experience with requirements management tools, workflow systems, and business process modelling tools such as MS Visio, Miro, and Draw.io.
• Hands-on experience producing and maintaining Requirements Traceability Matrices (RTMs) to link business requirements to functional specifications, design elements, test cases, and defects across the delivery lifecycle.
• Practical fluency with generative-AI tooling and prompt engineering, with the ability to design effective prompts for requirements analysis, document drafting, process modelling, test-case generation, and stakeholder summaries -and to critically evaluate AI-generated output before use in client deliverables.
• Working proficiency in SQL, with the ability to read and write moderately complex queries against operational and reporting databases to support data sampling, requirements validation, defect investigation, and User Acceptance Testing -without recourse to development-team support for routine analysis.
• Strong understanding of agile delivery practices, grounded in the principles of the Agile Manifesto, with practical hands-on experience operating within Scrum and Kanban frameworks -including ceremonies, backlog management, sprint planning, and continuous-flow techniques.
• Working knowledge of project management and change-control processes, with the ability to operate effectively in agile or hybrid delivery environments.
• Experience working in cross-functional teams with geographically distributed stakeholders.

AI-Native Delivery and Skill Orchestration:

• Practical understanding of an AI-native, skill-orchestrated BA operating model, in which typed demand intake and AI skills accelerate classification, strategy analysis, and specification drafting, while the analyst retains accountability for context, review, validation, and traceability.
• Ability to orchestrate and critically supervise AI-generated artefacts -recognizing that plausible output is not necessarily correct output -and to proportion human oversight to the maturity of each skill, applying heavier scrutiny to early-stage skills and a lighter touch to production-grade ones.
• Strong context-provision discipline: framing problems, assembling source material, and supplying the structured context that AI skills depend on to produce reliable, on-demand output -treating context as a first-class input rather than an afterthought.
• Comfort operating within a typed-intake, demand-ID-anchored traceability model and alongside adjacent AI-native roles (e.g., Context Engineers, Delivery Planners, and Product Managers) within a blended manual and AI-native delivery flow.

Product Engineering and Solution Design:

• Product-engineering literacy: a working understanding of solution architecture, APIs and integration patterns (REST, messaging, and EDI/EDIFACT), data models, and the software delivery lifecycle, sufficient to collaborate credibly with engineering teams, assess technical feasibility, and translate requirements into engineering-ready specifications.
• Ability to contribute to solution design and technical decision-making -reviewing data structures, interface contracts, and configuration options, and shaping non-functional requirements (performance, security, scalability, and auditability) alongside product engineering.
• Familiarity with engineering and delivery tooling -issue trackers and backlogs (e.g., Jira or Azure DevOps), API specification and testing tools, and version-controlled documentation -supporting close, hands-on collaboration with product engineering across the build cycle.

Qualifications

• Bachelor's degree in Business Administration, Information Systems, Supply Chain Management, or a related discipline.
• A relevant Master's degree or professional certification (e.g., CBAP, PMI-PBA, CSPO) is an asset.
• Relevant AI learning and certifications.