Lead PySpark Engineer As a Lead PySpark Engineer, you will design, develop, and optimise complex data processing solutions on AWS. You will work hands-on with PySpark, modernise Legacy data workflows, and support large-scale SAS-to-PySpark migration programmes. This role requires strong engineering discipline, deep data expertise, and the ability to deliver production-ready data pipelines within a financial services environment. Skill Profile: PySpark - P3 (Advanced) AWS - P3 (Advanced) SAS - P1 (Foundational) Key Responsibilities Technical Delivery Design, develop, and fix complex PySpark code for ETL/ELT and data-mart workloads. Convert and refactor SAS code into PySpark using SAS2PY tooling and manual optimisation. Build production-ready PySpark solutions that are scalable, maintainable, and reliable. Modernise and stabilise Legacy data workflows into cloud-native architectures. Ensure accuracy, quality, and reliability across data transformation processes. Cloud andamp; Data Engineering (AWS-Focused) Build and deploy data pipelines using AWS services such as EMR, Glue, S3, Athena. Optimise Spark workloads for performance, partitioning, cost efficiency, and scalability. Use CI/CD pipelines and Git-based version control for deployment and automation. Collaborate with engineers, architects, and stakeholders to deliver cloud data solutions. Core Technical SkillsPySpark andamp; Data Engineering 5+ years of hands-on PySpark experience (P3). Ability to write ..... full job details .....