(Senior) Data Analyst - Finance

Job description

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? What you will do: Partner closely with Finance team, Engineering and Business stakeholders to translate ambiguous questions into clear analytical deliverables. Analyze data (primarily financial), generate insights, and set up dashboards that convey them clearly and intuitively to stakeholders. Write production-grade SQL and Python to support analytics workflows and reusable analytical tooling. Design, build, document and maintain scalable data models using dbt (or Paradime) to support finance and cross-functional reporting needs. Automate data collection, cleaning, transformation, and deployment, ensuring data is reliably available for analysis. Contribute to data quality, testing, documentation, and engineering standards across the analytics stack. Mentor more junior team members on SQL, modeling best practices, and analytical rigor. Partner with a talented group of Data Engineers, Analysts, and Scientists, contributing to and learning from their diverse experience and skills. Who we´re looking for Bachelor's/ Master's / PhD in Economics, Computer Science, Data Science, Mathematics, Business Informatics, or a related quantitative field. Additional certifications are a plus (CFA etc.). Proven 5 years + experience in analytics or analytics engineering, ideally in a Finance, Fintech, or commercial context. Exposure to data science is a plus. Excellent programming skills in SQL and Python. Familiarity with version control (Git). Hands-on experience with dbt (or Paradime) and a solid understanding of data warehousing concepts and ETL bes…