We are looking for an experienced PySpark Developer with strong Microsoft Fabric and Azure engineering skills to join a major transformation programme within the financial-markets domain. This role is fully hands-on, focused on building and optimising large-scale data pipelines, dataflows, semantic models, and lakehouse components. Key Responsibilities Design, build and optimise Spark-based data pipelines for batch and streaming workloads Develop Fabric dataflows, pipelines, and semantic models Implement complex transformations, joins, aggregations and performance tuning Build and optimise Delta Lake / delta tables Develop secure data solutions including role-based access, data masking and compliance controls Implement data validation, cleansing, profiling and documentation Work closely with analysts and stakeholders to translate requirements into scalable technical solutions Troubleshoot and improve reliability, latency and workload performance Essential Skills Strong hands-on experience with PySpark, Spark SQL, Spark Streaming, DataFrames Microsoft Fabric (Fabric Spark jobs, dataflows, pipelines, semantic models) Azure: ADLS, cloud data engineering, notebooks Python programming; Java exposure beneficial Delta Lake / Delta table optimisation experience Git / GitLab, CI/CD pipelines, DevOps practices Strong troubleshooting and problem-solving ability Experience with lakehouse architectures, ETL workflows, and distributed computing Familiarity with time-series, market data,