Senior Data Platform Engineer

ppbABOUT THE COMPANY /b /p pDo 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. /p pWe are looking for a motivated and detail-oriented Senior Platform Data Engineer to join our growing data team. /p pbABOUT THE ROLE /b /p pAs 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. /p pbRESPONSIBILTIES /b /p pbData platform product delivery /b /p ul liDesign, build, test and operate scalable solutions in Microsoft Fabric and Azure, including OneLake, lakehouses, warehouses, notebooks, semantic models and pipelines. /li liBuild reusable ETL/ELT pipelines and transformations using Python, PySpark and SQL across SAP, databases, APIs, files and external-provider data. /li liDeliver governed data products for Group Sell-Out, Stock and Sell-In reporting, SAP decommissioning, analytics, AI and Copilot. /li liOptimise performance, storage and capacity, with effective monitoring, alerting, recovery, testing and release controls. /li /ul pbData quality, governance and operational ownership /b /p ul liEmbed automated quality controls, reconciliation and observability; resolve incidents through root-cause analysis and corrective action. /li liMaintain lineage, metadata, data contracts, source-to-target rules, business definitions, ownership, access controls and technical documentation. /li liOwn production reliability, runbooks and support procedures, balancing delivery speed with resilience, security, privacy and maintainability. /li /ul pbTechnical leadership and collaboration /b /p ul liTranslate business needs into clear technical scope, outcomes and acceptance criteria; communicate complexity, options, dependencies, risks and trade-offs in accessible language. /li liCollaborate closely with analysts, business owners, IT teams, National Organisations and partners, building trust across cultures and functions and creating shared accountability for outcomes. /li liFacilitate decisions, workshops and design reviews; listen actively, challenge constructively, manage expectations and elevate concerns early. /li liSet engineering standards, review architecture and code, mentor colleagues and promote documentation, knowledge sharing and continuous improvement. /li /ul pbPartner and vendor management /b /p ul liAct as the internal technical counterpart for partners, challenging solutions constructively and managing acceptance criteria, testing, defects, deployment and sign-off. /li liEnsure solutions are robust, documented, transferable and internally supportable, with effective knowledge transfer and reduced dependency on individual external resources. /li liReview and challenge proposed solutions to ensure alignment with business and technical requirements. /li liEnsure documentation, knowledge transfer and operational handover are completed to agreed standards /li /ul pbKEY REQUIREMENTS /b /p pbTechnical expertise /b /p ul liStrong hands-on experience with Microsoft Fabric, Azure data services, Python, PySpark, SQL and production ETL/ELT pipelines. /li liPractical knowledge of lakehouse and warehouse architecture, dimensional modelling, OneLake, semantic models and Power BI dependencies. /li liExperience integrating SAP, relational databases, APIs and file-based data, including XML, JSON, CSV and Parquet. /li liSound engineering practices covering Git, CI/CD, automated testing, environment management, monitoring, security, data quality and governance. /li liAbility to troubleshoot complex data, pipeline, performance and connectivity issues and to design maintainable, metadata-driven solutions. /li liKnowledge of the foundations for trustworthy AI: high-quality data, metadata, semantic models, business definitions, lineage, access controls, privacy and responsible-use principles. /li /ul pbCommunication, collaboration and ways of working /b /p ul liClear, concise communicator who adapts technical content for business, executive and engineering audiences. /li liStrong collaborator who can align diverse stakeholders, facilitate decisions, influence without authority and work effectively across international and cross-functional teams. /li liConstructive challenger with strong listening, negotiation and conflict-resolution skills; able to give and receive feedback openly. /li liDisciplined in documentation and knowledge transfer, with a service mindset and commitment to developing others. /li liStructured, pragmatic and evidence-led, balancing target architecture with business priorities across concurrent strategic initiatives. /li liHands-on and accountable, comfortable moving between architecture, implementation and production support. /li liProactive in identifying risks, dependencies and improvement opportunities, and decisive when priorities or requirements are unclear. /li /ul pbQUALIFICATIONS /b /p ul liDegree in Computer Science, Data Engineering, Information Systems, Software Engineering or a related field, or equivalent relevant professional experience. /li /ul pbPROFESSIONAL EXPERIENCE /b /p ul liFive to eight years progressive experience in data engineering, data-platform development or a closely related technical role. /li liProven ownership of production data pipelines and platforms across the full lifecycle, from requirements and architecture to deployment and support. /li liExperience in a multi-stakeholder environment involving analysts, business users, IT specialists and external providers. /li liExperience in retail, consumer goods, international organisations or SAP transformation is advantageous. /li /ul /p #J-18808-Ljbffr