Senior Data Platform Engineer

Do you want to work at the Heart of Sport, at the pulse of the global sporting goods industry, with the leading sport brands in the world? Then you need to join INTERSPORT.

We are looking for a motivated and detail-oriented Senior Platform Data Engineer to join our growing data team.

As a Senior Data Platform Engineer, you will design, build and operate INTERSPORT's Group Data Platform and trusted retail data products that power reporting, analytics and AI across the business. Working closely with data analysts and business stakeholders, you will develop scalable, reliable and governed data pipelines that transform Sell-Out, Sell-In and Stock data into actionable insights, enabling better decision-making and more efficient commercial operations.

You will play a key role in ensuring data is accessible, trusted and fit for purpose while supporting SAP modernisation and the responsible adoption of Microsoft Copilot and generative AI.

• Design, build, test and operate scalable solutions in Microsoft Fabric and Azure, including One Lake, lake houses, warehouses, notebooks, semantic models and pipelines.
• Build reusable ETL/ELT pipelines and transformations using Python, PySpark and SQL across SAP, databases, APIs, files and external-provider data.
• Deliver governed data products for Group Sell-Out, Stock and Sell-In reporting, SAP decommissioning, analytics, AI and Copilot.
• Optimise performance, storage and capacity, with effective monitoring, alerting, recovery, testing and release controls.

• Embed automated quality controls, reconciliation and observability; resolve incidents through root‑cause analysis and corrective action.
• Maintain lineage, metadata, data contracts, source‑to‑target rules, business definitions, ownership, access controls and technical documentation.
• Own production reliability, runbooks and support procedures, balancing delivery speed with resilience, security, privacy and maintainability.

• Translate business needs into clear technical scope, outcomes and acceptance criteria; communicate complexity, options, dependencies, risks and trade‑offs in accessible language.
• Collaborate closely with analysts, business owners, IT teams, National Organisations and partners, building trust across cultures and functions and creating shared accountability for outcomes.
• Facilitate decisions, workshops and design reviews; listen actively, challenge constructively, manage expectations and facilitate a collaborative culture.
• Set engineering standards, review architecture and code, mentor colleagues and promote documentation, knowledge sharing and continuous improvement.

• Act as the internal technical counterpart for partners, challenging solutions constructively and managing acceptance criteria, testing, defects, deployment and sign‑off.
• Ensure solutions are robust, documented, transferable and internally supportable, with effective knowledge transfer and reduced dependency on individual external resources.
• Review and challenge proposed solutions to ensure alignment with business and technical requirements.
• Ensure documentation, knowledge transfer and operational handover are completed to agreed standards.

• Strong hands‑on experience with Microsoft Fabric, Azure data services, Python, PySpark, SQL and production ETL/ELT pipelines.
• Practical knowledge of lakehouse and warehouse architecture, dimensional modelling, One Lake, semantic models and Power BI dependencies.
• Experience integrating SAP, relational databases, APIs and file‑based data, including XML, JSON, CSV and Parquet.
• Sound engineering practices covering Git, CI/CD,…