⭐ Role Overview
The Senior Growth Engineer sits at the intersection of marketing technology, data engineering, and product analytics, acting as a technical force multiplier for our Growth organization. Operating within the Growth Enablement team—the connective tissue of our squads—this high-ownership role is responsible for building the foundational systems that allow our Acquisition, Activation, Retention, Sales, and Partnerships squads to move faster, measure better, and experiment with confidence.
You are equally comfortable discussing causal inference models and writing production-grade data pipelines. You will drive architecture decisions, introduce AI-augmented workflows, manage complex tracking taxonomies, and set the technical quality bar for measuring what is notoriously hard to measure in an ambiguous, privacy-constrained world.
⭐ How will you make an impact?
- Marketing Technology & Integrations: Build and maintain robust server-to-server (S2S) integrations with major ad platforms (Meta CAPI, Google S2S, AppsFlyer) and own end-to-end web/app tracking parity, smart script inserts, and SKAN setup.
- Tracking Standards & Governance: Own the overarching Marketing Tracking Standards (event naming conventions, schema versioning, consent management tooling), acting as the final technical authority on tracking implementation quality.
- Attribution Product Engineering: Engineer and refactor the data infrastructure feeding our attribution models, connecting ad-platform spend APIs, matching session data, and piping profit/gross margin data back to ad networks to enable value-based bidding.
- AI-Powered Growth Engineering: Productionise ML models from notebook prototypes to monitored pipelines (CLTV scoring, causal impact tooling, non-trackable conversion models) and build AI-assisted tools like automated anomaly detection on spend or LLM-powered taxonomy systems.
- Sales Tech & AI Tooling Enablement: Build pipeline infrastructure for lead scoring, intent signal enrichment, and CRM data quality, while owning the integration layer for Sales-side AI experimentation tools (e.g., ElevenLabs, Supersonic, TDO, Moon Scale).
- Signal Enhancement: Implement advanced matching, first-party data enrichment, and probabilistic matching to maximize signal quality as third-party tracking continues to degrade.
- Cross-Squad Collaboration: Act as the technical point of contact for individual Growth squads, unblocking integration roadblocks, reviewing their instrumentation, and proactively replacing bespoke solutions with scalable, shared platform infrastructure.
- Codifying Knowledge: Document architectural decisions, integration patterns, and data standards to ensure institutional growth knowledge is structured, accessible, and built to scale over time.
⭐ What makes you a great fit?
- Production-Grade Software Engineering: You write clean, tested, and maintainable code, applying software design principles and Domain-Driven Design (DDD) thinking to growth and data systems.
- Distributed Systems Fluency: You are highly confident shipping integrations across REST APIs, webhooks, and event streaming, and you know how to architect around the failure modes of distributed networks.
- Modern Tracking Landscape Expertise: You possess a deep understanding of browser and in-app consent frameworks, cookie-less measurement, server-side tagging, and the technical implications of privacy changes (iOS, etc.) on attribution.
- Data & Pipeline Fluency: You speak the same language as Data Engineers and Analysts. You can write complex SQL, architect robust data models, build pipelines, and maintain an exceptional standard for data reliability.
- Commercial Stakeholder Management: You comfortably interface with revenue-facing teams (Sales, Partnerships, Growth Director) and seamlessly translate commercial hypotheses into precise technical requirements.
- Applied AI & ML Competency: You know how to wrap an ML model to make it trustworthy in production, with a sharp focus on monitoring, drift detection, fallback logic, and clear ownership.
- AI-Assisted Development: You actively leverage the frontier of modern AI engineering tooling (LLMs, embeddings, vector search, AI-assisted coding frameworks) with the engineering judgment to apply them where they add true proof of value.
⭐ How can you earn extra bonus points?
- Familiarity with causal inference methods (difference-in-differences, synthetic control, uplift modelling).
- Prior experience building or scaling shared platform infrastructure in high-growth consumer or B2B SaaS businesses.
- Deep technical implementation experience with modern tag management and data activation systems (e.g., Rudderstack, HubSpot, or equivalents).
🏠 Remote Flexibility: The freedom to work from home any day that works for you.
🌴 Time to Recharge: 25 working days of paid vacation and Jornada Intensiva in August..
💊 Alan Health Insurance: Premium health, dental, and mental health support via Alan. Pre-existing conditions are covered.
😋 Meal Perk: €150/month allowance on your Alan card + 50% off Ametller Origen prepared dishes at the office.
💸 Tax-Free Savings: Increase your take-home pay by using Flexible Remuneration for extra meal costs (up to €70/mo) and public transport (up to €136/mo).
🖥️ Home Office Gear: We provide a table, ergonomic chair, and monitor for your home setup.
🇪🇸 Language Learning: Free Spanish classes.
🤑 Referrals: Cash rewards for bringing in new talent.
🌟 Social Life: Daily office breakfast and monthly team events
🎯 Dynamic Hub: A high-energy, inclusive environment designed for collaboration and connection with a team that represents over 60 countries.
*Benefits offered may differ based on the type of contract that is issued
So, what are you waiting for? Apply now!
All applications and CVs must be submitted in English 😉
Skills Required
- Production-grade software engineering with clean, tested, maintainable code and DDD thinking
- Design and implement server-to-server integrations and API work (Meta CAPI, Google S2S, AppsFlyer)
- Experience with SKAN, server-side tagging, tag management and browser/in-app consent frameworks
- Strong SQL skills and experience architecting and building reliable data pipelines and data models
- Productionise ML models: monitoring, drift detection, fallback logic, and monitored pipelines
- Experience with REST APIs, webhooks, and event streaming architectures
- Experience building attribution, matching session data, and connecting ad-platform spend APIs
- Ability to work with commercial stakeholders (Sales, Partnerships, Growth) and translate hypotheses into technical requirements
- Familiarity with LLMs, embeddings, vector search and AI-assisted engineering tooling
- Familiarity with causal inference methods (difference-in-differences, synthetic control, uplift modeling)
- Prior experience with Rudderstack, HubSpot, or modern tag management/data activation systems
- Experience building or scaling shared platform infrastructure in high-growth consumer or B2B SaaS
What We Do
Lodgify is a constantly growing tech start-up, focused on building vacation rental software that enables vacation rental owners to independently manage and market their business online. We do so by providing them with easy-to-build websites, including a booking and reservation system, various synchronisation options, and payment collection options. We are +300 Lodgifiers strong, and you can find us working in Barcelona and all around the world! We are working in a hybrid mode and provide our team members with an option to work from home and spend additional time with their family, friends and pets. With nearly 50 nationalities, we celebrate diversity daily! With 43% of female and 57% of male employees we are striving to establish a gender balance. Actions are continuously taken to include more women in our Tech teams.








