Business & Data Analyst

The Business Analyst is responsible for translating operational needs into clear, testable data, BI, and digital solutions across shipping operations, technical, crewing, procurement, finance, and commercial functions. The role covers the full delivery lifecycle, including discovery, requirements definition, validation, UAT, implementation, and user adoption. AI tools are used to accelerate the work, while the Business Analyst remains accountable for business logic, accuracy, and the quality of information presented to decision-makers.

Job description:

• Lead interviews, workshops, and process walkthroughs with business stakeholders.
• Map business processes, identify pain points, and define practical future-state solutions.
• Translate business needs into requirements, KPIs, business rules, data definitions, user stories, and acceptance criteria.
• Define and validate the expected behavior of AI and natural-language analytics solutions, including limitations and escalation conditions.
• Develop and execute evaluation scenarios to identify inaccurate or misleading AI-generated answers before release.
• Use SQL to investigate data, validate assumptions, reconcile discrepancies, and confirm reported figures.
• Review data models, source-to-target mappings, data lineage, and granularity to ensure reliable results.
• Support access, privacy, security, and data-governance requirements for analytics and AI solutions.
• Collaborate with developers, data engineers, QA, and BI developers throughout the delivery lifecycle.
• Lead UAT, coordinate business approval, and support rollout, training, and user adoption.

Requirements:

• 3+ years of practical experience as a Business Analyst, Product Analyst, or Systems Analyst, preferably working on Data, BI, or enterprise-system projects.
• Strong hands-on SQL skills, including joins, aggregations, and window functions.
• Proven experience in requirements gathering, leading requirements sessions, and translating business needs into clear and actionable deliverables.
• Good understanding of data models, source systems, data lineage, granularity, and data-quality gaps.
• Working knowledge of BI concepts, including dimensional modelling, measures, dimensions, and KPI definition.
• Experience using AI tools, with the ability to critically evaluate and validate AI-generated outputs.
• Experience working in an Agile environment, using Azure DevOps, Jira, or similar backlog-management tools.
• Strong analytical and structured thinking, attention to detail, sound professional judgment, and commitment to data accuracy.
• Experience with Microsoft Fabric, Power BI, Power Apps, or Power Automate – an advantage.
• Experience with LLM evaluation, prompt design, RAG, or agentic systems – an advantage.
• Experience in maritime, logistics, or another operational industry – an advantage.