Provide detail landscape design patterns, capturing network, solution components for On-prem application
Setup data engineering practice and ways of working (aligning with DevOps)
Setup and maintain development environment and mature it.
Deliver code and capability.
Manage code quality and software quality.
Support and mentor snr. developers.
To do this successfully you will:
Have experience designing and implementing data solutions on Azure cloud platform
Ensure all technical solutions are designed in alignment with the organisation’s technical boundaries through ongoing consultation with Solution Architects
Create designs that address relevant areas of complexity and provide a fully considered and detailed solution design across the technology portfolio
Ensuring that uniform enterprise-wide application design standards are maintained
Provide technical leadership throughout the design and deployment life cycle and focus on delivery of quality solutions
Develop deployment of automation using automation tools and scripts to provide a fully functional cloud stack in Azure
Provide input to the project estimation process to include the identification of required resource types, potential utilisation, geographical availability and allocation, as well as effort and schedules for the technical components across the technology portfolio.
To be successful in this position you will have
Experience in software design and architecture in the Data & Analytics domain
Experience of working in the Azure Data environment
Experience in the Insurance or Financial Services industry preferred
Extensive experience of working in Agile (Scrum) and Waterfall/ Hybrid
Hands-on experience in Azure stack (Azure Storage (Datalake Gen 2), Azure Data Factory, Azure Databricks, Azure SQL Server MI, Azure Synapse, Azure DevOps, Azure MLOps, Azure Cosmos)
Integration experience and leadership in development of API, API orchestration and integration using batch-based files in data and ML environment
Experience in cloud engineering including deploying infrastructure as code
Data tools, Entity Relationship modelling, metadata systems, data quality tools and techniques, BI and reporting
Knowledge of architectural patterns and software design patterns, with demonstrable experience applying the patterns to solution design
