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.