Join our Global Network Analytics area This is a role for someone who enjoys working close to data, understands both technical quality and business context, and wants to have a real impact on how data is prepared, validated and used by analytical, reporting and product teams. As a (Senior)  Data Developer  you will help transform data into a trusted foundation for decision-making, reporting and automation. You will combine technical engineering skills with business understanding, data quality awareness and a critical approach to AI-supported work In this role, you will: Design, build and maintain ETL/ELT processes using SQL, PySpark and Python, including integration of data from different source systems.  Develop data layers in Databricks, Data Lake and Delta Lake , including tables, views and data models used by analytical, reporting and automation solutions. Automate and orchestrate data loading and transformation processes to reduce manual work, improve repeatability and lower the risk of errors.  Ensure data quality, consistency and reliability through validation rules, monitoring, alerting and incident diagnosis. Optimize SQL queries, Spark processes and data storage structures with a focus on performance, stability, scalability and processing costs.  Provide reliable, ready-to-use data to analysts, Product Owners and other stakeholders as a foundation for analysis, reporting and automation Create and maintain technical documentation in Confluence, covering data processes, models, KPI logic, dependencies, data lineage and incident-handling procedures   Use AI tools consciously as a work accelerator, while fully verifying generated code, configurations and documentation before implementation.