Senior Marketing Data Analyst

About ApprovalMax ApprovalMax provides end-to-end accounts payable automation for businesses using cloud accounting systems such as Xero and QuickBooks Online. We have 20,000+ businesses worldwide across 70+ countries, and strong product-market fit built over 8+ years. Our customers, accountants, bookkeepers, and finance teams are risk-averse, non-technical users who rely on us to control how money leaves their business. Remote — applicants must be based in the UK, Portugal, Serbia or Moldova. Role Overview: Reporting to the Head of Analytics, you will own the analytical relationship between the Data Team and the Marketing function. This is a dual role, you will do serious analytical work, building the models, dashboards, and insights Marketing relies on, and you will own how Marketing uses data, setting the rhythms, SLAs, and standards that make analytics a genuine partner to the business rather than a service desk. The measurement layer underneath Marketing (attribution, tracking taxonomy, UTM standards, the HubSpot property schema, and the definitions behind the funnel numbers) has grown organically and needs to be rebuilt deliberately. You will be the person who does that, and then keeps it honest. This isn’t a role where you’ll be handed a brief and asked to execute. You’ll help shape how embedded analytics works at ApprovalMax, with real influence over the model from day one. 8 0% marketing analytics, 20% wider data contribution, including mentoring, standards and best practices across the business. Key Responsibilities: Marketing Analytics Own the analytical relationship with the Marketing function: understand their priorities, anticipate their data needs, and deliver analysis that drives decisions rather than merely informing them. Build and maintain the core dashboards, reports, and models Marketing relies on, and take responsibility for their accuracy, freshness, and usability. Own the analysis behind the funnel that matters most to the business: visitor → free trial → paid conversion, trial nurture performance, lifecycle-stage progression, and the leading indicators that move them. Quantify channel and campaign performance end to end (spend, CAC, payback, pipeline contribution and retained revenue) rather than stopping at platform-reported conversions. Translate ambiguous business questions into clear analytical frameworks; make assumptions explicit and deliver useful outputs before perfect data is available. Bring cross-functional context to Marketing analysis, combining product usage, subscription revenue, and CRM data to surface insights a channel-level view would miss. Attribution & Measurement Own the rebuild of marketing attribution: agree the model with Marketing and Finance, document its assumptions and known blind spots, and implement it in the warehouse so that one number is produced once and reused everywhere. Reconcile platform-reported numbers (ad platforms, GA4, HubSpot) against warehouse truth, and be the person who can explain — credibly and repeatedly — why they differ. Build the measurement approach for activity that attribution cannot see cleanly: brand, organic, partner and word-of-mouth. Incrementality and holdout testing where the spend justifies it. Design and analyse marketing experiments — landing pages, nurture sequences, pricing and packaging messages — including how success is defined before the test runs. Tracking Architecture & Data Collection Standards Diagnose the tracking we already have, not just the tracking we intend to build: read the existing client-side implementation, cookie and local-storage handling, and referrer behaviour to work out why a channel is misreporting. Our largest single attribution problem today is an oversized Direct segment, and unpicking it is an early priority for this role. Own the event taxonomy: what we track, what each event means, what properties it carries, and what it is allowed to be used for. Own the Google Tag Manager container (tags, triggers, va