Senior Data Analyst
- Firma
- Nordic Knots
- Lokacija
- Remote
- Nivo
- Senior
- Objavljeno
- 29.09.2026
Opis posla
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Strategy & Business Development
·
Stockholm
Senior Data Analyst
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.
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.
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.
The Role & What You'll Do
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.
Key Responsibilities:
• 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.
• 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.
• 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.
• New Metrics & Definitions: Dig into potential new metrics, dimensions, and definitions together with Finance and the commercial teams, and build them into our systems so we can answer questions we have not been able to answer before.
• Complex Analysis: Support and lead more complex analysis projects across assortment, pricing, demand, channel performance, and profitability.
• AI Initiatives: Take part in and lead AI initiatives within the organization, from agentic analytics and automation to identifying and building the use cases with real business value.
• Data Accessibility: Make data more accessible across the organization through documentation, self-service, and enablement so that team members can answer their own questions with confidence, at the highest possible quality.
• End-to-End Ownership: As part of a small team, you own your area from groundwork to strategy including the hands-on parts, such as data cleaning and mapping and quick turnarounds on ad-hoc requests from the business.
Who You Are
Most importantly, you are commercially curious and quality-obsessed. You are not satisfied with a query that runs; you want a number that is right and a definition the business agrees on. You are pragmatic, take real ownership of your domain, and enjoy an environment where you can see the impact of your work quickly.
We believe you have:
• Analytics Background: 5+ years of experience as a data analyst, BI developer, analytics engineer, or similar. Ideally from retail, e-commerce, consumer goods, or another data-rich commercial environment.
• Technical Craft: Strong SQL and solid, hands-on experience with modern cloud data warehousing, data modelling, and BI tooling. You know how to build a data model t