Platform Architecture and Engineering responsibilities:Design and implement scalable Databricks Lakehouse platforms on AWS and/or Azure aligned to client requirementsArchitect end-to-end data platforms including ingestion, storage (Delta Lake), processing, and consumption layersBuild and configure cloud infrastructure using infrastructure-as-code (e.g. Terraform and Declarative Automation Bundles(DAB''s Establish secure, compliant environments including networking (VNet/VPC, Private Link), identity (IAM/Entra ID), data governance (Unity Catalog), and access controlsDefine environment strategies (dev/test/prod), CI/CD pipelines, and release processes for Databricks deploymentsImplement monitoring, logging, cost optimisation, and performance tuning across the platformDesign and implement data pipelines using Delta Live Tables, Auto Loader, and Databricks Workflows for both batch and streaming workloadsClient Delivery and Enablement responsibilities:Work directly with clients to translate business and technical requirements into scalable platform designsLead technical workshops, architecture sessions, and whiteboarding engagements with client stakeholdersSupport rapid prototyping and proof-of-concept builds within Databricks to demonstrate platform capabilities and accelerate client adoptionProvide best practice guidance on Lakehouse architecture, data modelling, workload optimisation, and cost managementProduce high-quality technical documentation including architecture diagram