Senior Tracking & Attribution Engineer (Server-Side Tracking) | Stape + Triple Whale

Project Overview We are looking for an experienced tracking and attribution expert to build a highly advanced server-side tracking infrastructure for our German e-commerce business. The core challenge is the length and complexity of our customer journey. Customers often interact with multiple marketing touchpoints and may return to the website days or even weeks later before completing a purchase. Typical return scenarios include: – Manually re-entering the website URL – Returning via bookmarks – Comparing products over multiple sessions – Revisiting after interacting with different marketing channels Our average customer journey spans approximately 3–6 weeks before conversion. The objective is to create a robust attribution infrastructure that preserves original attribution data across long timeframes and complex redirect chains — ensuring we no longer lose attribution and incorrectly classify users as Direct Traffic. Scope of Work / Infrastructure Setup The project includes setting up: – Client-side tracking containers – Server-side tracking containers – Advanced attribution persistence mechanisms – Stape Store–based attribution persistence setup – Tracking integrations via Stape and Taggers – Triple Whale attribution integration and synchronization The tracking infrastructure must ensure that: – Original UTM parameters remain accessible across long customer journeys – Attribution persists regardless of redirects or session expiration – All downstream tools and events can reliably access original acquisition data – Marketing attribution remains stable even after multiple revisits – Triple Whale receives clean and reliable attribution data from the server-side infrastructure The goal is to establish a top-tier tracking infrastructure that prevents unattributed traffic and significantly improves attribution accuracy across all marketing channels. Current Marketing Channels The attribution setup must support and properly track interactions across: – Google Ads – Meta Ads – Taboola / Native Advertising – Klaviyo (Email Marketing) – Idealo.de – Advertorial publishers – ADCELL (Affiliate Marketing) Current Challenges: Approximately 50% of our traffic is currently classified as "Direct Traffic," which heavily distorts attribution across our paid and owned marketing channels. Key challenges include: – Loss of original UTM parameters over time – Multiple redirect layers (advertorials, publishers, affiliate redirects) – Affiliate tracking dependencies – Cookie consent limitations – Browser tracking restrictions – Long decision-making cycles – Multi-touch customer journeys Previously tested solutions such as Triple Whale and Klar have not delivered satisfactory results in their default configurations. Project Objectives The ideal solution should: – Reduce Direct Traffic attribution below 10% – Establish clean and reliable multi-channel attribution – Build a scalable and sustainable tracking infrastructure – Implement advanced server-side tracking architecture – Improve identity resolution and attribution persistence – Support advanced Google tagging and attribution models – Integrate Stape/Taggers tracking architecture with Triple Whale attribution – Enable long-term "virtual session" attribution across extended customer journeys The system should make it possible to identify previous marketing touchpoints even when users return directly after days or weeks. Expected Outcome: We are looking for a long-term, scalable attribution infrastructure that: – Preserves attribution data across extended customer journeys – Minimizes unattributed traffic – Provides accurate channel reporting – Improves ROAS evaluation across all marketing channels – Creates a future-proof tracking foundation for further growth – Delivers reliable attribution data into Triple Whale and other downstream analytics tools