Senior Analytics Engineer - Brand Analytics (all genders)

About our Product & Tech Department

Our mission is to digitize the classic shopping stroll, turning it into a personalized, inspiring experience for every customer. Technology and data sit at the center of everything we build. We are not a fashion company with a tech team on the side. Tech drives our product, our strategy, and our growth.
Our proprietary tech stack powers our own shops and SCAYLE, our commerce infrastructure solution that serves over 350 brands globally. Same foundation, bigger stage. The challenges keep things interesting.

What To Expect

The Brand Analytics team is the insights engine: its mission is to empower data-driven decision-making for Retail Media Partners by providing a single source of truth. This creates a powerful opportunity for brands to gain deep performance visibility and turn enterprise-scale data into actionable growth strategies.

While operating within an existing ecosystem, the architectural transition from a single monolith into four specialized product teams provides a highly autonomous, greenfield-like environment where your decisions will directly shape our future state and enable us to multiply our Retail Media revenue.

• Design, build, and maintain production-grade analytical data transformations and metrics definitions within Google BigQuery to enable robust performance and budget reporting for our bidding marketplaces
• Establish rigorous, automated data validation frameworks and schema checks to shield public-facing reporting dashboards and analytical tables from upstream variance or structural drift
• Lead the migration of complex analytical transformation rules and data aggregation queries directly out of historical legacy application repositories into modular, decoupled analytics environments
• Partner with Data Engineers to engineer clean data modeling boundaries around shared catalog assets (such as products and brands) that connect the decentralized product stack with core platform endpoints
• Set analytics engineering standards, direct code-reuse conventions, and establish reusable data blueprints within the team

Who You Are

• Expert in designing modular and performance-optimized analytical data models, and building scalable incremental transformations
• Advanced SQL mastery and extensive native experience within cloud-based big data platforms (e.g. Google BigQuery)
• Practical working familiarity with modern workflow orchestrators like Dagster to synchronize data assets and event-driven pipeline schedules
• Extensive experience writing declarative data checks, regression validation assertions, and data quality tests to enforce strict metric definition compliance
• Proficiency with Git version control, structured code review flows, and automated deployment infrastructure like GitLab CI/CD pipelines
• A structural developer who excels at transforming loose business descriptions into highly structured, reliable, and standardized metrics environments
• Able to cleanly convey complex database schemas, transformation choices, and analytical definitions to software developers
• Highly driven to establish data blueprints within a technical greenfield context

Nice To Have:
 

• Data Transformation Tooling: Practical, hands-on experience utilizing dbt (Data Build Tool) for managing version-controlled analytical modeling codebases, validation schemas, and deployment workflows
• Domain Expertise: Prior experience working within an eCommerce, retail tech, or ad-tech ecosystem, with a solid understanding of web analytics tracking, funnel parameters, or ad performance metrics

Salary range

70k - 85k €