EU remote
Senior Analytics Engineer-Commercial Intelligence
About this role
Ready to lead, disrupt and reinvent the sleep industry? We are Emma – The Sleep Company . Founded in 2015, we have grown into the world’s largest direct-to-consumer (D2C) sleep brand, with a presence in over 20 markets and more than 35 Emma stores across Europe. Our mission is simple: to develop sleep comfort products that empower our customers to awaken their best every day. Today, our products are trusted by millions and recommended by leading consumer associations worldwide.
It’s our people who bring this mission to life. At Emma , you’ll join a driven, international team that values ownership, collaboration, and continuous knowledge sharing. With colleagues from over 70 nationalities, we combine diverse perspectives with a shared ambition to learn, grow, and create lasting impact, together. Ready to awaken your best with us? You'll join the Commercial Intelligence team, a cross-functional, domain-focused team of Analytics Engineers, Data Engineers and Data Analysts.
The team owns profitability metrics for the entire business. It is also taking its first steps in bringing website and revenue data together, so we can see the full funnel from first visit to final margin. Roles in the team have fluid borders. You won't hand work over a wall. You'll pick up tasks from your teammates, and they'll pick up yours. You'll build with dbt and Redshift, own what you ship, and help shape how we use AI in and around our data work.
What you will do: Own the T in ELT within the Commercial Intelligence domain, from raw data to trusted, analysis-ready models. Make data modelling decisions based on Kimball's design principles, and help the team apply them consistently. Extend the core data warehouse model with new data points. You'll start with profitability metrics and connect web analytics and revenue data into one funnel view. Work closely with Data Engineers and Data Analysts in one team.
You'll pick up ingestion, pipeline and analysis work when the team needs it, and share your modelling knowledge in return. Support development with and around AI. That includes using AI tools to speed up your own engineering work, and building well-documented, reliable data foundations that AI use cases can build on. Ensure data integrity, consistency and security. Set up proactive data monitoring and alerting. Build strong relationships with stakeholders in E-Commerce, Marketing and other commercial teams, and with upstream and downstream data teams.