Data Analyst PLG (Remote Europe)

n8n is a workflow automation platform that uniquely combines AI capabilities with business process automation. We give technical teams the flexibility of code with the speed of no-code, backed by a passionate community of builders. With 500+ integrations and fair-code principles, we're revolutionizing how businesses connect their systems and processes.

We were founded end of 2019 and currently:

• 🧑‍🤝‍🧑 We’re a diverse team of + 120 talented people

• 🚀 Our annual recurring revenue is growing over 7x year-over-year

• ⭐️ With +118k GitHub stars, we are in the top 50 most popular projects of all time on Github

• 🍾 We were the 25th fastest growing startup last year and 4th BtoB SaaS Rising 100 this year in Europe according to Sifted

• 🌱 We were Sequoia's first seed investment in Germany, and most recently secured our $60M Series B (February '25, led by Highland)

Join n8n to help us unlock the next level of product-led growth through data.

At n8n, we’re building the most powerful automation platform for technical teams. Our unique blend of low-code flexibility and full-code control gives builders unmatched speed and scalability — backed by one of the world’s most active developer communities. We're building a self-serve motion that’s already powering millions of automations across companies of all sizes. Now, we’re looking for a sharp and curious PLG & Growth Data Analyst to help us deeply understand and optimize our self-serve user funnel — from acquisition through expansion.

🎯 Your main goal will be to enable data-driven ARR growth by uncovering insights that optimize self-service user acquisition, activation, retention, and expansion.

To get there, here’s how you’ll make an impact:

🔍 Become the expert on our PLG funnel

• Understand the current self-serve user journey, from signup to expansion, and map drop-off points.

• Own and evolve our PLG funnel analytics to track activation, conversion, retention, and monetization.

• Conduct quarterly business reviews and funnel performance analyses to identify trends and risks.

🧪 Power experimentation and growth

• Analyze the results of PLG experiments and advise teams on what’s working — and what’s not.

• Continuously refine our PQL definitions based on behavioral signals and user segmentation.

• Evaluate pricing plan performance across user segments and surface monetization opportunities.

🛠 Build tools that make data accessible and actionable

• Design and maintain dashboards that track self-serve KPIs and enable rapid decision-making.

• Build and scale self-service tools and documentation to help teams answer product and growth questions.

• Partner with product, marketing, and analytics to ensure shared metrics and clarity across the funnel.

🤝 Enable cross-functional success

• Work closely with Product, Growth, Marketing, and Engineering teams to inform their priorities with data.

• Serve as a trusted partner in shaping PLG strategy by identifying new opportunities for activation and expansion.

• Champion a culture of experimentation and data-informed decision-making across n8n.

REQUIREMENTS

Must-haves

• 🧠 Self-serve PLG analytics experience: You have 4–5 years in data roles at high-growth B2B SaaS companies with a strong self-serve motion. You’ve directly analyzed user behavior across the activation, monetization, and retention funnel, and have helped shape the product strategy through PQL models, funnel mapping, and in-product experimentation.

• 📐 Experimental mindset: You’ve proposed, designed, and analyzed experiments that drove tangible growth outcomes.

• 🗣️ Cross-functional communication: You’re known for translating complex data into crisp insights that influence Product, Marketing, and Engineering teams.

• 🧮 Strong analytical toolkit: You’re highly proficient in SQL and experienced with BigQuery, DBT, Metabase, and Google Sheets.

• 🤖 Bias for automation & AI: You’re excited about using automation and AI to streamline workflows and unlock new insights.

• 📚 Academic foundation: You hold a Master’s degree in a quantitative field (e.g. Computer Science, Statistics, Economics, or similar).

Nice-to-haves

• 👾 Experience in devtool or community-led growth environments: You understand the