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Manager Data, Insights, Analytics & Reporting

WESTAY
Dubai, UAE
Fulltime
Mid-Senior
2 months ago
CPACRMGit
Free

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1. Data Strategy, Architecture & Governance

  • Define and own WESTAY’s enterprise data strategy, architecture, and roadmap, aligned with commercial, brand, product, and operational priorities
  • Lead the design and evolution of WESTAY’s first-party data layer across web, app, CRM, booking, and operational systems
  • Establish data governance, taxonomy, definitions, lineage, and quality standards across all functions
  • Ensure compliance with GDPR, CCPA, and relevant global privacy and data protection regulations
  • Partner with engineering and product to embed data-by-design principles into every digital and operational touchpoint

2. Analytics Integration, Tagging & Tracking Infrastructure

  • Lead end-to-end deployment, maintenance, and QA of analytics and tracking infrastructure including:
  • Tag management systems (GTM, server-side tagging)
  • Web and app analytics (GA4, Adobe Analytics, Mixpanel, Amplitude or equivalents)
  • Conversion APIs and offline conversion uploads
  • Cookieless and consent-aware measurement frameworks
  • Own the data layer specification, event taxonomy, and parameter governance across all digital properties
  • Ensure tracking accuracy, redundancy, and resilience across paid media, organic, CRM, and product analytics
  • Manage analytics vendors, technology partners, and implementation agencies with clear KPIs and accountability

3. Business Intelligence, Reporting & Visualization

  • Build and own WESTAY’s enterprise BI and reporting ecosystem, delivering trustworthy, self-serve insight at every level of the business
  • Design executive, commercial, brand, product, and operational dashboards using modern BI stacks (Looker, Tableau, Power BI, Mode or equivalents)
  • Establish a single source of truth for KPIs across revenue, bookings, marketing performance, customer, and operations
  • Define reporting cadences, SLAs, and narrative briefings for the leadership team
  • Champion data literacy, visualization standards, and self-serve analytics across the organization
  • 4.
  • Data Science, Advanced Analytics & Predictive Modeling
  • Build and lead WESTAY’s data science capability, applying statistical, machine learning, and AI techniques to commercial and customer challenges
  • Develop predictive and prescriptive models including:
  • Demand forecasting and dynamic pricing inputs
  • Customer lifetime value and churn prediction
  • Propensity, segmentation, and next-best-action models
  • Marketing mix and incrementality modeling
  • Design and run experimentation programmes (A/B, multivariate, causal inference) across product, marketing, and operations
  • Operationalize models into decisioning, personalization, and CRM activation in partnership with engineering and martech

5. Customer, Market & Industry Insights

  • Lead WESTAY’s customer and market insights agenda, fusing first-party behavioural data, qualitative research, and third-party industry intelligence
  • Build a continuous intelligence engine covering competitive benchmarking, destination trends, traveller sentiment, and luxury lifestyle signals
  • Surface trends, white-space opportunities, and demand shifts across hospitality, aviation, yachting, and adjacent luxury categories
  • Translate data into clear, narrative-led insights that inform strategy, product, brand positioning, and commercial planning
  • Partner with PR, brand, and partnerships teams to shape data-driven thought leadership and proprietary industry reports
  • 6.
  • Data Platform, Engineering Partnership & AI Enablement
  • Partner with engineering and product to design and scale the modern data platform — data warehouse / lakehouse, ELT pipelines, reverse ETL, CDP, and ML infrastructure
  • Champion the adoption of AI and generative AI tooling for analytics acceleration, internal copilots, and insight automation
  • Build and lead a high-performing team across analytics engineering, BI, data science, and insights, while orchestrating external specialists where appropriate
  • Establish operating rituals — backlog management, prioritisation frameworks, and stakeholder partnership models — that turn data into a strategic asset
  • Define and manage the data and analytics budget with clear ROI and business impact tracking

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