CRM Data Analyst

Role overview A CRM Data Analyst role focused on transforming customer, transactional, and behavioural data into clear insights that improve CRM, loyalty, and customer engagement outcomes. The position partners with data engineering, analytics, CRM, and operations teams to evaluate campaign performance, audience behaviour, and customer economics in high-volume consumer environments. It suits an analytically rigorous professional who is comfortable shaping ambiguous briefs and explaining findings to both technical and non-technical stakeholders.

Responsibilities - Analyse CRM, transactional, loyalty, app, and behavioural datasets to evaluate campaign and customer performance at a granular level. - Translate analytical findings into practical recommendations and concrete business actions for CRM, marketing, and operations stakeholders. - Collaborate with Data Engineering, Analytics, CRM, Loyalty, and Operations teams to scope questions, source data, and deliver insight. - Design queries, dashboards, and analyses that measure audience segmentation, personalisation, and lifecycle engagement effectiveness. - Take open-ended or ambiguous briefs and independently define the most appropriate analytical approach and methodology. - Maintain high standards for data quality, accuracy, and analytical rigour across all outputs and reporting.

Requirements - Significant experience in a data or CRM analyst role, ideally supporting CRM, customer engagement, or marketing teams. - Strong SQL and data manipulation skills, with hands-on experience working in modern data stacks or customer data platforms. - Proven ability to analyse transactional, behavioural, and customer datasets and translate them into clear, actionable insight. - Excellent stakeholder management and communication skills, able to explain complex analyses to varied audiences. - Comfortable taking ambiguous briefs and independently shaping the analytical approach end to end. - Collaborative mindset with a track record of working across data, CRM, loyalty, and operations functions.

Nice to have - Experience in quick-service restaurants, casual dining, retail, hospitality, or other high-volume consumer environments. - Background analysing loyalty programmes, customer lifetime value, or wider customer economics. - Familiarity with customer data platforms, digital analytics tools, or modern data stack technologies. - Experience working with restaurant or store-level performance data. - Knowledge of experimentation, incrementality testing, or campaign measurement methodologies.

Benefits and work setup - Remote-first working arrangement, allowing the analyst to work from their preferred location. - Distributed, international team with colleagues across multiple regions. - Emphasis on ownership, growth, and clear career progression pathways. - Regular team meetups and in-person events designed to build strong working relationships. - Bring-your-own-device policy for everyday work.