Data Analyst

About the role

FITT Meals is looking for a Data Analyst to turn customer, subscription, product, marketing and operational data into actionable insights. The role sits in the Technology team and works closely with Marketing, Product, Customer Experience, Operations, Finance and senior leadership to support data‑driven decision making across the business.

Key responsibilities

• Analyse the full customer journey – acquisition, onboarding, activation, engagement, renewal, pause, cancellation, win‑back and referral.
• Identify behaviour patterns, segments and friction points that impact conversion, retention and lifetime value.
• Measure and explain subscription metrics such as churn, renewal, reactivation, cohort performance, CLV and ARPU.
• Build cohort, funnel, segmentation and behavioural analyses to inform product, pricing, menu and promotion decisions.
• Develop churn indicators and support predictive models to flag at‑risk or high‑potential customers.
• Write, optimise and maintain advanced SQL queries on large datasets using Google BigQuery.
• Create reusable datasets, views and analytical models with consistent metric definitions.
• Investigate data anomalies, reconcile conflicting sources and perform root‑cause analysis.
• Collaborate with data engineering to improve data models, pipelines, tracking and documentation.
• Use GA4 to analyse website and app behaviour, traffic sources, conversion funnels, events, attribution and campaign performance.

Required profile

• Proven experience analysing customer behaviour and subscription‑based businesses.
• Strong ability to write efficient SQL for large, complex datasets.
• Hands‑on experience with Google BigQuery and GA4.
• Commercial mindset with curiosity to translate data into practical recommendations.
• Comfort working cross‑functionally with product, marketing, operations and finance teams.

Required skills

• SQL
• Google BigQuery
• GA4 (Google Analytics 4)
• Statistical methods such as hypothesis testing, correlation analysis, forecasting and experiment evaluation