Data Analytics Engineer

Tekla makes high-quality home textiles, with a focus on craftsmanship, sustainability, and timeless design. We sell through our own e-commerce platform, our stores in Copenhagen and London, and wholesale partners around the world. As we grow across channels and markets, we are building the operational and technological foundation to support that growth.

We are looking for a Data Analytics Engineer to bring our data in-house and build the foundation the whole company relies on. This is a new role and our first dedicated data hire. Today an external partner builds and runs our data platform. You will take it over, own it end to end, and shape how everyone at Tekla works with data and AI.

Reporting to the Technology Lead, you will form Tekla's core technology team together. Data only creates value when it drives action, so you will spend a good share of your time with colleagues across the business, making sure what you build answers real questions and becomes part of how people work. In your first year, the priority is to bring the data foundation in-house, then to support analytics, then to open up data to AI.

Day to day, you will work with ecommerce and marketing on attribution, tracking, and channel reporting; merchandising and planning on product, stock, and sales data; finance on reporting and reconciliation against the ERP; retail and wholesale on store and B2B performance; and operations on demand, supply, and warehouse data. During the transition you will also work closely with our data partner, and with our commerce platform and ERP partners.

This is a full-time position based in Copenhagen, Denmark. The role sits in our open-plan office, working closely with the wider team day to day.

Key responsibilities include, but are not limited to:

Data foundation

• Lead the handover of our data platform from our external partner, covering pipelines, warehouse, and semantic layer.
• Own extraction and ELT pipelines, currently in Weld, from our ERP, Medusa, and marketing platforms into BigQuery.
• Own the dbt project: dimensional models, tests, documentation, and CI/CD.
• Own the semantic layer, currently in Power BI, and help decide its future direction.
• Monitor data quality across systems, so data arrives complete and accurate.
• Make sure data is stored, accessed, and shared in line with data protection law, including when AI tools use it.

Analytics support

• Work with colleagues across the business to turn their questions into well-defined models and metrics.
• Extend the data foundation with new models and metrics as the business needs them.
• Help teams build dashboards and analyses in Power BI, Mixpanel, and Claude that lead to better decisions.