Roles andamp; Responsibilities Lead and mentor a high-performing data engineering team, providing hands-on technical guidance across Databricks (DLT), PySpark, Python, SQL, and Azure Data Factory. Architect, build, and optimize scalable data pipelines and platforms to support high-volume trading and analytics workloads. Drive performance tuning, cost optimization, and best-practice engineering standards within Databricks and cloud data environments. Own end-to-end technical delivery-ensuring reliability, quality, and timely execution of data projects in a fast-paced trading context. Act as the technical SME for modern data engineering, contributing to data strategy, solution design, and platform enhancements. Collaborate closely with trading, product, and platform teams to translate business requirements into robust data solutions. Promote engineering excellence through code reviews, automation, DevOps practices, and continuous improvement initiatives. Foster a culture of knowledge sharing through community activities, training, and thought leadership within the data engineering domain. Ensure smooth execution of change management, incident management, and problem resolution processes. Mandatory Skills Cloud Platforms: AWS/Azure/SAP - Master ELT Pipelines:Master Data Modelling:Master Data Integration andamp; Ingestion:Master Data Manipulation andamp; Processing:Skilled DevOps andamp; Version Control: GitHub, GitHub Actions, Azure DevOps - Skill