Web Analyst

This role owns advertising tracking end-to-end, making the full path from ad click to CRM lead to sale visible and reliable. It sits at the intersection of web analytics, marketing and product: not just setting up a Pixel or UTM and handing it to a developer, but understanding what exactly is measured, where data leaks, and how to keep the funnel transparent and trustworthy.

Tasks

* End-to-end ad tracking: audit and develop the full chain ads → site → Pixel/CAPI → CRM → deal → payment. * Meta Ads infrastructure: set up and maintain Meta Ads, Datasets, Events and the Conversions API, controlling event delivery and quality. * Data consistency: keep UTM, click IDs, deduplication and data accuracy aligned across ads, site and CRM. * Find and fix data losses and discrepancies. * Integrations: work with APIs, webhooks, n8n and other integration tools. * Debug tracking and find where and why data delivery breaks. * Monitor Meta's platform changes and adapt the system ahead of time. * Assess how tracking and attribution quality affect ad performance and business results. * Prioritize improvements by their impact on metrics. * Work across marketing, product and development.

* Middle+ level with 5+ years of commercial experience in web/marketing analytics and ad tracking. * Strong hands-on experience with Meta Pixel, Events and the Conversions API. * A solid grasp of attribution, UTM, click IDs and data flow from ads to CRM and final conversion. * Experience with APIs, webhooks and n8n or similar tools. * You find the root cause of tracking issues yourself, not just work from specs. * Business sense: you assess the impact of analytics on business results, not only technical correctness. * Basic understanding of GTM, dataLayer and client-side tracking. * AI tools are part of your daily work. * English B1 or higher.

Google Ads, GA4, server-side tracking, amoCRM/Kommo, SQL, Python/JavaScript, experience with other ad platforms.

Conditions

* Full remote on an international product. * A set-up stack and clear onboarding. * An AI-native team: AI tools are part of the whole team's workflow. * A large product with real data volume and complex funnels. * A small team, short decision chains and low bureaucracy.

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