ASAP: Lead Data Analyst - Commercial Finance (m/w/d)

Overview In this 20-week interim role, you will design, build and deploy an automated EMEA revenue dashboard. You will consolidate data from multiple channels, develop scalable data models, and create impactful visuals for senior stakeholders. The role focuses on data quality, governance, and efficient reporting, partnering with Finance, Commercial Analytics, and Data Engineering to deliver a high-impact analytics solution. You will work in a fast-paced environment to drive measurable improvements in revenue analytics and reporting accessibility. This opportunity offers high visibility and immediate business impact with a hybrid setup in Zurich. Leistungen / Benefits 20-week interim assignment high visibility with senior stakeholders hybrid working model in Zurich (2-3 days onsite) immediate business impact Verantwortungsbereiche Lead design, build, and deployment of an automated EMEA omnichannel revenue dashboard Consolidate data from multiple commercial channels and markets Develop scalable data models and semantic layers for reporting Create dashboards and visualisations for senior stakeholders Translate business requirements into analytics solutions through stakeholder engagement Drive automation to improve reporting efficiency and data accessibility Ensure data quality, governance, and reporting accuracy Collaborate with Finance, Commercial Analytics, Data Engineering, and stakeholders to deliver successfully Zentrale Anforderungen 5+ years in Data Analytics, BI, Commercial Analytics, or Financial Analytics Strong SQL and advanced analytical techniques Proven experience building automated dashboards and executive reporting Experience designing semantic layers and scalable data models for BI Hands-on data visualization experience; Looker knowledge is a plus Exposure to cloud platforms, ideally GCP and BigQuery Understanding of revenue analytics and business KPIs Experience in retail or consumer goods is advantageous Excellent communication to influence diverse stakeholders Self-starter, able to deliver quickly in a fast-paced environment excellent communication stakeholder engagement self-motivation SQL Looker semantic layers