Key Responsibilities
1. Lead the selection and implementation of data infrastructure technologies, such as Data Lakes, Warehouses, Lakehouses, orchestration tools, and streaming platforms.
2. Design and evolve the enterprise data architecture including integration with Databricks Data Lake Data Factory.
Ai enablement collaborate with AI teams architect solutions supporting machine learning operations predictive analytics intelligent automation
platform strategy define implement engineering standards best practices governance frameworks architectural blueprints for dataplatform ecosystem Stakeholder engagement partner business units product owners engineering teams translate strategic goals into scalable datasolutions Innovation Optimisation evaluate emerging technologies recommend enhancements improve performance cost efficiency resilience dataplatform Security Compliance ensure datarchitecture adheres daa compliance standards GDPR EEA residencyrequirements Enterprise scale workEnterprise Dev Ops Cloud Engineering ensureinfrastructure code CI CD monitoring practicessitewide Mentorship guide upskilldata engineers analysts best practisedataplatform pipeline design cloudnative development Skills Experience proven experiencearchitectingdaplatforms Microsoft AzureincludingDatabricksDataLakeStorageGen2AzureDataFactory Strong understandinglakehousetechnologyDeltaLakedata pipelines PySparkSQL SkillexperienceAI workflows ML workflowsmodel lifecycle managementintegrationdatapipelines Stron under standingshowed history citizenadevelopmented governments