Your contribution:

You will design, build and operate data pipelines and products on Azure Databricks, integrating SAP and non-SAP sources across finance, sales, e-commerce, supply chain and after-sales.

You will develop reliable finance data products covering EBITDA, cost of goods sold, intercompany pricing, inventory and liquidity, including multi-currency logic and reconciliation with group consolidation systems.

You will model after-sales data at individual watch level, enabling detailed reporting on repairs, service performance and serial-number-based metrics.

You will build and release business applications on top of the data platform, including real-time executive dashboards and web and mobile applications for sales teams at the point of sale.

You will develop, deploy and continuously improve machine learning models, including product image recognition and recommendations to help identify watches with the highest sell-through potential at each point of sale.

You will lead root-cause analysis when figures differ between systems, communicate findings to Finance and business stakeholders, and drive data corrections at source.

You will own the release lifecycle of data products and applications, including version control, code reviews, hotfixes, feature releases, application distribution and user access management.

You will support system migrations and the decommissioning of legacy solutions, ensuring data accuracy through structured validation and reconciliation.

You will implement proactive data quality monitoring to maintain reliable data and minimise business impact.

You will evaluate and recommend new technologies and solutions, including AI-assisted development, to continuously improve our data and application landscape.

You will fit well to our squad if:

You have at least 5 years of experience in data engineering, analytics engineering or business intelligence, with hands-on experience delivering production-ready data products.

You hold a Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems or a related field.

You have strong practical experience with Azure Databricks, including PySpark, SQL, Delta Lake, Unity Catalog and Delta Live Tables.

You have experience working with SAP data, ideally across SD, MM, FI/CO and customer service, and integrating it with e-commerce, CRM, retail POS and after-sales systems.

You have delivered finance data products in a multi-entity, multi-currency environment, including FX conversion, cost price logic and reconciliation with consolidation platforms such as CCH Tagetik, SAP BPC or OneStream.

You have built and deployed business applications for end users, including web and mobile front ends, APIs and application distribution through app stores or enterprise device management.

You have developed and operationalised machine learning models, from training data and deployment to ongoing monitoring.

You have experience delivering near real-time data to applications and dashboards.

You have strong programming skills in Python and SQL and are comfortable working with Git-based development and release processes.

You can translate business needs into reliable technical solutions and communicate effectively with non-technical stakeholders, including senior leadership.

You speak English fluently.

It would be an advantage if:

You have in-depth knowledge of the luxury watch or retail industry, including wholesale and boutique channels, sell-in and sell-out, point-of-sale performance and after-sales service.

You have experience working in a multi-brand group.

You have experience with Power BI semantic models and reports.

You are familiar with cross-border or headless e-commerce platforms.