About the role
From the employer’s listing · Nordic Knots · posted 8 September 2026
<p><span>Nordic Knots is building a global Scandinavian design house for the modern home. Starting with hand-crafted rugs, the brand has expanded rapidly into new home categories including textiles, curtains, and bedroom collections. As we scale across markets, channels, and product categories, the volume and complexity of our data is growing just as fast and we are looking for an entrepreneurial, business-minded Senior Data Analyst to join our team in Stockholm.</span></p><p><span>This is not a reporting only role. We need a builder and an owner: someone who understands the business behind the numbers, who is just as comfortable debugging a broken data model as explaining a margin development to the commercial team, and who is genuinely excited about what AI can do for how a company works with its data. You will be the person the organization trusts when asking "is this number right?" and the person who makes sure the answer is yes.</span></p><p><span>We are a small team, and that shapes the role in the best way: the scope is broad, you own your domain end to end, and you are close enough to the business to see your work turn into decisions fast.</span></p><h5><span>The Role & What You'll Do</span></h5><p><span>Working closely with Finance, Tech, Operations, Buying & Merchandising, and the commercial teams in the US, UK, and Sweden, you will take ownership of our business intelligence layer: the data warehouse, the business logic within it, and the quality of what comes out of it. You will also take a leading role in bringing AI into how we work with data.</span></p><p><span><strong>Key Responsibilities:</strong></span></p><ul><li><p><span>Business Intelligence Reporting Logic: Own the reporting logic and technical implementation behind our reporting, making sure the numbers our KPIs are built on are correct, consistent, and reliable. KPI definitions sit with our Finance team; you are the person who makes sure the data behind them holds up.</span></p></li><li><p><span>Data Warehouse & Data Models: Maintain and develop our data warehouse and the business model logic within it, including new sources, structural changes, and the continuous updates that follow a fast-growing product and market portfolio.</span></p></li><li><p><span>Data Quality & Root Causes: Profile and monitor our data quality, find the errors before the business does, and drive the work of tracing issues back to their root cause in our source systems together with the teams that own them.</span></p></li><li><p><span>New Metrics & Definitions: Dig into potential new metrics, dimensions, and definitions together with Finance and the commercial teams, and build them into our syste