Business Analyst

Business Analyst

About Wedded Wonderland

Wedded Wonderland is a leading luxury wedding, travel, and lifestyle media platform, inspiring audiences through exceptional wedding celebrations, destination experiences, and creative content. We connect couples, industry professionals, and global audiences through engaging digital media, editorial features, and innovative experiences across the wedding and travel industries.

We are looking for a highly technical and proactive Business Analyst to help drive our continued growth by improving systems, streamlining business processes, and leveraging AI and automation to create smarter, more efficient ways of working.

Role Overview

We are hiring a Business Analyst to take ownership of how our systems, data, and processes work together across Wedded Wonderland. This role goes beyond traditional business analysis. You will be responsible for identifying opportunities, designing solutions, implementing automations, improving reporting, and ensuring our teams have the tools and systems they need to perform effectively.

You will act as the bridge between business operations and technology, turning complex business challenges into practical, scalable solutions. From improving CRM systems and workflows to building AI-powered solutions, integrations, and dashboards, you will play an important role in enhancing our operational efficiency and supporting business growth.

We are looking for someone with an AI-first mindset who is hands-on, technically capable, solution-oriented, and proactive in finding ways to improve how the business operates.

Key responsibilities

AI-led delivery (day to day)

• Use AI tools (e.g. Claude, ChatGPT, Copilot, Zia) daily to speed up requirements, documentation, analysis, testing and build work.

• Design and deploy AI-powered workflows: agents, assistants, classification, summarisation, data enrichment and AI-generated content inside business systems.

• Write, test and maintain prompts and prompt templates; evaluate AI output for accuracy, tone and risk before it reaches staff or customers.

• Connect AI models to business systems through APIs, MCP servers and automation platforms.

• Proactively identify where AI can replace manual tasks, and measure time saved.

• Keep up with new AI tools and features, run quick pilots and recommend what to adopt.

• Apply responsible AI practice: data privacy, access control, human review and clear usage guidelines.

Business analysis (functional and technical)

• Run stakeholder workshops and interviews to capture requirements, pain points and success criteria.

• Map current-state and future-state processes; identify gaps, waste, automation and AI opportunities.

• Write clear BRDs, functional specs, user stories, acceptance criteria and technical specs (data models, field mappings, API and integration logic).

• Translate business needs into system configuration and build-ready designs, and validate delivered work against requirements.

Data analysis and business intelligence

• Clean, audit and maintain data quality across CRM and operational systems (duplicates, picklists, field hygiene, ownership).

• Build and maintain dashboards, KPIs and recurring reports for leadership and operational teams.

• Use AI-assisted analysis to surface trends, insights and recommended actions.

• Write queries and data transformations to support reporting and decision-making.

Project management

• Plan and deliver system and process projects end to end: scope, timeline, risks, dependencies and sign-off.

• Run sprints, stand-ups and status updates; keep tasks, priorities and blockers visible.

• Manage multiple concurrent workstreams and re-prioritise quickly as business needs change.

Automation and integration

• Design and build workflow automations, blueprints and custom functions (e.g. Zoho Deluge, Make.com scenarios, GoHighLevel workflows).

• Build and maintain integrations between platforms using APIs, webhooks and connectors.

• Identify and implement AI and automation opportunities that remove manual work.

• Monitor automations for failures and fix them quickly.

Tech stack management and system administration

• Administer core platforms: users, roles, profiles, permissions, modules, layouts, fields and templates.

• Maintain the tech stack inventory, licences, access and vendor relationships; recommend tools to add, consolidate or retire.

• Own change management: test in sandbox, document changes and release safely.

• Handle tier-2 system support and troubleshooting for internal users.

Training, documentation and best practice

• Create SOPs, user guides, process maps and training materials for every system or process change, using AI to produce and maintain them faster.

• Deliver onboarding and refresher training to staff, live and recorded.

• Define and enforce system, data and AI standards, naming conventions and governance; train staff to use AI tools effectively and safely.

Team management

• Lead, guide and review the work of junior analysts, admins or offshore support staff.

• Allocate tasks, set priorities and quality-check output.

• Coach team members and contribute to hiring and onboarding new team members.

Requirements

Skills and experience

Must have

• 3–5 years in a business analyst, systems analyst or business systems role, covering both functional and technical BA work.

• Demonstrated daily use of AI tools (Claude, ChatGPT, Copilot or similar) to accelerate analysis, documentation and build work, with examples to show.

• Hands-on experience building AI-powered automations: calling LLM APIs, prompt engineering, and embedding AI steps into workflows (e.g. via Make.com, Zoho Flow or n8n).

• Sound judgement on AI output quality, data privacy and when human review is needed.

• Hands-on administration of at least one major CRM (Zoho CRM strongly preferred; Salesforce or HubSpot considered).

• Proven experience building workflow automations and integrations (APIs, webhooks, JSON, low-code tools such as Make.com, Zapier or Zoho Flow).

• Strong data skills: Excel / Google Sheets (advanced), SQL or similar query language, and a BI tool (Zoho Analytics, Power BI, Looker Studio or Tableau).

• Experience managing projects with defined scope, timelines and stakeholders, using tools such as Zoho Projects, Jira or Asana.

• Experience writing requirements, user stories, process maps (BPMN or swimlane) and SOPs.

• Experience delivering user training and supporting adoption of new systems.

• Excellent written and spoken English.

Nice to have

• Scripting experience (Zoho Deluge, JavaScript or Python).

• Advanced AI experience: building AI agents, MCP servers, RAG / knowledge-base assistants or multi-step AI workflows.

• Experience across the wider Zoho One suite (Desk, Recruit, Creator, Sprints, Learn, Cliq).

• Google Workspace and Microsoft 365 administration.

• Prior experience leading or mentoring a small team.

• Experience supporting Australian businesses or working with remote teams across time zones.

• Relevant certification (e.g. Zoho CRM Certified Administrator, IIBA ECBA/CCBA, PMP/CAPM, Agile/Scrum, or an AI/LLM course).

What we're looking for

• AI-first mindset. Your default question is "how can AI make this faster or better?", and you back it with working solutions.

• Strong communicator. You explain technical ideas in plain language, write clearly, ask the right questions and keep stakeholders informed without being chased.

• Highly organised. You juggle many requests, prioritise by impact and urgency, and keep your work documented and traceable.

• Fast turnaround. You move quickly, deliver in iterations and don't let small tasks sit.

• Multi-dimensional problem solver. You consider the process, the people, the data and the system together, not just the immediate symptom.

• Solution- and process-driven. You bring a recommended fix, not just a problem, and you design repeatable processes rather than one-off workarounds.

• Ownership mindset. You take responsibility end to end, from requirement to adoption, and work well with limited supervision.

How success is measured

• Requests and projects delivered on time and to agreed requirements.
  

• Measurable reduction in manual work through automation and AI.
  

• Number of AI use cases deployed into day-to-day operations, and hours saved.
  

• Improved data quality and reporting accuracy across systems.
  

• Stable, well-documented systems with fewer recurring support issues.
  

• Staff adoption of systems and AI tools, measured through training completion and usage.
  

• A productive, well-led team with clear priorities and quality output.