Senior Data Platform Engineer

INTERSPORT, the worldwide hub for sport‑related merchandise, is expanding its data organisation and seeks a Senior Data Platform Engineer. The role sits within a fast‑growing data squad and is responsible for shaping the Group Data Platform that underpins reporting, analytics and artificial‑intelligence initiatives throughout the company. Every day the engineer will craft, test and run scalable solutions on Microsoft Fabric and Azure, employing OneLake, lakehouses, data warehouses, notebooks and semantic models. They will construct reusable ETL/ELT flows with Python, PySpark and SQL that pull together sell‑out, sell‑in and stock information from SAP, databases, APIs and a variety of file types. The position also covers performance tuning, capacity planning, monitoring, alerting and release management, while embedding automated quality checks, lineage tracking and comprehensive documentation. Close collaboration with analysts, business owners, IT groups and national partners is required to translate needs into clear technical scopes, run workshops, set engineering standards and mentor colleagues. Partner and vendor interactions involve reviewing solutions, managing testing, handling defects and ensuring smooth hand‑over to internal support. The candidate must bring solid hands‑on experience with Microsoft Fabric, Azure data services, Python, PySpark and SQL, as well as practical knowledge of lakehouse and warehouse design, OneLake, semantic models and Power BI dependencies. Proven ability to integrate SAP, relational databases, APIs and common file formats such as XML, JSON, CSV and Parquet is essential. Sound engineering habits, including Git, CI/CD pipelines, automated testing, environment control, monitoring, security and data‑governance, are required, together with strong troubleshooting skills for complex pipeline and connectivity issues. Understanding of trustworthy‑AI foundations, high‑quality data, metadata, lineage, access controls and responsible‑use principles, is also expected. Effective communication across business, executive and technical audiences, collaborative stakeholder management, disciplined documentation and a proactive, evidence‑driven mindset are key behavioural traits. A university degree in a relevant discipline or equivalent experience, plus five to eight years of progressive data‑engineering work where full‑lifecycle ownership of production pipelines has been demonstrated, complete the core profile. Experience in retail, consumer‑goods environments, large international organisations or previous SAP transformation projects is considered an advantage. The role offers the chance to influence a global data platform, work with cutting‑edge AI tools such as Microsoft Copilot, and develop within a multicultural, high‑impact team. What the role asks for: - Hands‑on experience with Microsoft Fabric, Azure data services, Python, PySpark and SQL - Knowledge of lakehouse/warehouse architecture, OneLake, semantic models and Power BI - Ability to integrate SAP, databases, APIs and XML/JSON/CSV/Parquet files - Proficiency in Git, CI/CD, automated testing, monitoring, security and data‑governance - Skill in troubleshooting complex pipelines and designing metadata‑driven solutions - Strong communication for business, executive and engineering audiences - Five to eight years progressive data‑engineering experience owning production pipelines - Retail, consumer‑goods or SAP transformation experience (nice‑to‑have)