Data Analyst - Finance

<div><strong style="font-size: 24px;">Ready to lead, disrupt and reinvent the sleep industry?</strong></div> <div> <p><span data-contrast="auto">We are <strong>Emma – The Sleep Company</strong>. 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. </span></p> </div> <div> <p><span data-contrast="auto">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. </span></p> </div> <div> <p><span data-contrast="auto">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. </span></p> </div> <div> <p><strong><span data-contrast="auto">Ready to awaken your best with us?</span><span data-ccp-props="{}">&nbsp;</span></strong></p> </div> <div>&nbsp;</div><br><strong>What you will do:</strong><br><div> <li>Partner closely with Finance team, Engineering and Business stakeholders to translate ambiguous questions into clear analytical deliverables.&nbsp;</li> <li>Analyze data (primarily financial), generate insights, and set up dashboards that convey them clearly and intuitively to stakeholders.&nbsp;</li> <li>Write production-grade SQL and Python to support analytics workflows and reusable analytical tooling.&nbsp;</li> <li>Design, build, document and maintain scalable data models using dbt (in Paradime) to support finance and cross-functional reporting needs.&nbsp;</li> <li>Automate data collection, cleaning, transformation, and deployment, ensuring data is reliably available for analysis.&nbsp;</li> <li>Contribute to data quality, testing, documentation, and engineering standards across the analytics stack.&nbsp;</li> <li>Mentor more junior team members on SQL, modeling best practices, and analytical rigor.&nbsp; &nbsp;</li> <li>Partner with a talented group of Data Engineers, Analysts, and Scientists, contributing to and learning from their diverse experience and skills.&nbsp;&nbsp;</li> </div><br><strong>Who we´re looking for</strong><br><div> <li>Required Qualifications 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, CFI etc.)&nbsp;</li> <li>Proven 3+ years of experience in analytics or analytics engineering, ideally in a Finance, Fintech, or commercial context. Exposure to data science is a plus.&nbsp;</li> <li>Excellent programming skills in SQL and Python.&nbsp;</li> <li>Familiarity with version control (Git).</li> <li>Strong experience with at least one major BI/visualization tool: Tableau, Power BI, or equivalent.&nbsp;</li> <li>Hands-on experience with dbt and a solid understanding of data warehousing concepts and ETL best practices.</li> <li><span data-teams="true">Previous experience with Paradime is a plus.&nbsp;</span></li> <li>Experience working with modern cloud data warehouses (Redshift etc) is a plus .&nbsp;</li> <li>Strong q