Methods Business and Digital TechnologyPosted 2 weeks ago

Principal Microsoft Fabric Architect and Technical Lead

Methods Business and Digital TechnologyPosted 2 weeks ago

On-siteLondon, England, United Kingdom or Edinburgh, Scotland, United Kingdom

London, England, United Kingdom or Edinburgh, Scotland, United KingdomOn-siteFull TimeSenior LevelMedium

Full TimeSenior LevelMedium

Job Summary

Define technical direction, priorities, and standards for the Data Transformation Programme, chairing architecture reviews and governing data platform standards. Lead complex data migration projects from legacy systems to modern cloud-native platforms, designing end-to-end solutions including APIs, real-time streams, and modern data services. Mentor architects and engineers while establishing engineering practices and developing Fabric knowledge within Methods and client teams. This role requires flexibility to travel to client sites and offices in London, Sheffield, and Bristol, with a predominantly remote schedule. Candidates must demonstrate deep expertise in Fabric architecture, the Azure data stack, and modern data modeling, with a proven track record in terabyte-scale migrations and streaming architectures.

Required Qualifications

Deep knowledge of Fabric architecture, governance, OneLake, Real-Time Intelligence, Data Engineering, Warehousing and Power BI integration
Capability to influence senior stakeholders, programme sponsors and project boards
Ability to communicate technical decisions to non-technical executives and secure agreement on technical direction
Deep knowledge of the Azure data stack (Azure SQL Server, CosmosDB, Azure Data Factory, Purview, Synapse, Event Hub, Azure Databricks/Fabric)
Extensive data modelling experience: both normalised relational models and de-normalised Star Schema/dimensional models
Excellent relational database design skills with expertise in diagnosing and optimising performance across SQL Server, PostgreSQL, and cloud databases
Proven track record with complex data migration projects (terabyte+ datasets, multiple legacy source systems, structures and unstructured data)
Proficiency with Parquet/Delta Lake or other modern data storage formats
Experience with streaming architectures using Kafka, Event Hubs, or Kinesis for real-time data processing
Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines
Experience processing and managing unstructured data types (text, images, logs, sensor data)
Understanding of Lambda and Kappa architectural patterns and when to apply each
Deep knowledge of Fabric architecture, governance, OneLake, Real-Time Intelligence, Data Engineering, Warehousing and Power BI integration
Capability to influence senior stakeholders, programme sponsors and project boards
Ability to communicate technical decisions to non-technical executives and secure agreement on technical direction
Deep knowledge of the Azure data stack (Azure SQL Server, CosmosDB, Azure Data Factory, Purview, Synapse, Event Hub, Azure Databricks/Fabric)
Extensive data modelling experience: both normalised relational models and de-normalised Star Schema/dimensional models
Excellent relational database design skills with expertise in diagnosing and optimising performance across SQL Server, PostgreSQL, and cloud databases
Proven track record with complex data migration projects (terabyte+ datasets, multiple legacy source systems, structures and unstructured data)
Proficiency with Parquet/Delta Lake or other modern data storage formats
Experience with streaming architectures using Kafka, Event Hubs, or Kinesis for real-time data processing
Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines
Experience processing and managing unstructured data types (text, images, logs, sensor data)
Understanding of Lambda and Kappa architectural patterns and when to apply each
Deep knowledge of Fabric architecture, governance, OneLake, Real-Time Intelligence, Data Engineering, Warehousing and Power BI integration
Capability to influence senior stakeholders, programme sponsors and project boards
Ability to communicate technical decisions to non-technical executives and secure agreement on technical direction
Deep knowledge of the Azure data stack (Azure SQL Server, CosmosDB, Azure Data Factory, Purview, Synapse, Event Hub, Azure Databricks/Fabric)
Extensive data modelling experience: both normalised relational models and de-normalised Star Schema/dimensional models
Excellent relational database design skills with expertise in diagnosing and optimising performance across SQL Server, PostgreSQL, and cloud databases
Proven track record with complex data migration projects (terabyte+ datasets, multiple legacy source systems, structures and unstructured data)
Proficiency with Parquet/Delta Lake or other modern data storage formats
Experience with streaming architectures using Kafka, Event Hubs, or Kinesis for real-time data processing
Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines
Experience processing and managing unstructured data types (text, images, logs, sensor data)
Understanding of Lambda and Kappa architectural patterns and when to apply each
Deep knowledge of Fabric architecture, governance, OneLake, Real-Time Intelligence, Data Engineering, Warehousing and Power BI integration
Capability to influence senior stakeholders, programme sponsors and project boards
Ability to communicate technical decisions to non-technical executives and secure agreement on technical direction
Deep knowledge of the Azure data stack (Azure SQL Server, CosmosDB, Azure Data Factory, Purview, Synapse, Event Hub, Azure Databricks/Fabric)
Extensive data modelling experience: both normalised relational models and de-normalised Star Schema/dimensional models
Excellent relational database design skills with expertise in diagnosing and optimising performance across SQL Server, PostgreSQL, and cloud databases
Proven track record with complex data migration projects (terabyte+ datasets, multiple legacy source systems, structures and unstructured data)
Proficiency with Parquet/Delta Lake or other modern data storage formats
Experience with streaming architectures using Kafka, Event Hubs, or Kinesis for real-time data processing
Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines
Experience processing and managing unstructured data types (text, images, logs, sensor data)
Understanding of Lambda and Kappa architectural patterns and when to apply each
Deep knowledge of Fabric architecture, governance, OneLake, Real-Time Intelligence, Data Engineering, Warehousing and Power BI integration
Capability to influence senior stakeholders, programme sponsors and project boards
Ability to communicate technical decisions to non-technical executives and secure agreement on technical direction
Deep knowledge of the Azure data stack (Azure SQL Server, CosmosDB, Azure Data Factory, Purview, Synapse, Event Hub, Azure Databricks/Fabric)
Extensive data modelling experience: both normalised relational models and de-normalised Star Schema/dimensional models
Excellent relational database design skills with expertise in diagnosing and optimising performance across SQL Server, PostgreSQL, and cloud databases
Proven track record with complex data migration projects (terabyte+ datasets, multiple legacy source systems, structures and unstructured data)
Proficiency with Parquet/Delta Lake or other modern data storage formats
Experience with streaming architectures using Kafka, Event Hubs, or Kinesis for real-time data processing
Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines
Experience processing and managing unstructured data types (text, images, logs, sensor data)
Understanding of Lambda and Kappa architectural patterns and when to apply each
Deep knowledge of Fabric architecture, governance, OneLake, Real-Time Intelligence, Data Engineering, Warehousing and Power BI integration
Capability to influence senior stakeholders, programme sponsors and project boards
Ability to communicate technical decisions to non-technical executives and secure agreement on technical direction
Deep knowledge of the Azure data stack (Azure SQL Server, CosmosDB, Azure Data Factory, Purview, Synapse, Event Hub, Azure Databricks/Fabric)
Extensive data modelling experience: both normalised relational models and de-normalised Star Schema/dimensional models
Excellent relational database design skills with expertise in diagnosing and optimising performance across SQL Server, PostgreSQL, and cloud databases
Proven track record with complex data migration projects (terabyte+ datasets, multiple legacy source systems, structures and unstructured data)
Proficiency with Parquet/Delta Lake or other modern data storage formats
Experience with streaming architectures using Kafka, Event Hubs, or Kinesis for real-time data processing
Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines
Experience processing and managing unstructured data types (text, images, logs, sensor data)
Understanding of Lambda and Kappa architectural patterns and when to apply each
Deep knowledge of Fabric architecture, governance, OneLake, Real-Time Intelligence, Data Engineering, Warehousing and Power BI integration
Capability to influence senior stakeholders, programme sponsors and project boards
Ability to communicate technical decisions to non-technical executives and secure agreement on technical direction
Deep knowledge of the Azure data stack (Azure SQL Server, CosmosDB, Azure Data Factory, Purview, Synapse, Event Hub, Azure Databricks/Fabric)
Extensive data modelling experience: both normalised relational models and de-normalised Star Schema/dimensional models
Excellent relational database design skills with expertise in diagnosing and optimising performance across SQL Server, PostgreSQL, and cloud databases
Proven track record with complex data migration projects (terabyte+ datasets, multiple legacy source systems, structures and unstructured data)
Proficiency with Parquet/Delta Lake or other modern data storage formats
Experience with streaming architectures using Kafka, Event Hubs, or Kinesis for real-time data processing
Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines
Experience processing and managing unstructured data types (text, images, logs, sensor data)
Understanding of Lambda and Kappa architectural patterns and when to apply each
Deep knowledge of Fabric architecture, governance, OneLake, Real-Time Intelligence, Data Engineering, Warehousing and Power BI integration
Capability to influence senior stakeholders, programme sponsors and project boards
Ability to communicate technical decisions to non-technical executives and secure agreement on technical direction
Deep knowledge of the Azure data stack (Azure SQL Server, CosmosDB, Azure Data Factory, Purview, Synapse, Event Hub, Azure Databricks/Fabric)
Extensive data modelling experience: both normalised relational models and de-normalised Star Schema/dimensional models
Excellent relational database design skills with expertise in diagnosing and optimising performance across SQL Server, PostgreSQL, and cloud databases
Proven track record with complex data migration projects (terabyte+ datasets, multiple legacy source systems, structures and unstructured data)
Proficiency with Parquet/Delta Lake or other modern data storage formats
Experience with streaming architectures using Kafka, Event Hubs, or Kinesis for real-time data processing
Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines
Experience processing and managing unstructured data types (text, images, logs, sensor data)
Understanding of Lambda and Kappa architectural patterns and when to apply each
Deep knowledge of Fabric architecture, governance, OneLake, Real-Time Intelligence, Data Engineering, Warehousing and Power BI integration
Capability to influence senior stakeholders, programme sponsors and project boards
Ability to communicate technical decisions to non-technical executives and secure agreement on technical direction
Deep knowledge of the Azure data stack (Azure SQL Server, CosmosDB, Azure Data Factory, Purview, Synapse, Event Hub, Azure Databricks/Fabric)
Extensive data modelling experience: both normalised relational models and de-normalised Star Schema/dimensional models
Excellent relational database design skills with expertise in diagnosing and optimising performance across SQL Server, PostgreSQL, and cloud databases
Proven track record with complex data migration projects (terabyte+ datasets, multiple legacy source systems, structures and unstructured data)
Proficiency with Parquet/Delta Lake or other modern data storage formats
Experience with streaming architectures using Kafka, Event Hubs, or Kinesis for real-time data processing
Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines
Experience processing and managing unstructured data types (text, images, logs, sensor data)
Understanding of Lambda and Kappa architectural patterns and when to apply each
Deep knowledge of Fabric architecture, governance, OneLake, Real-Time Intelligence, Data Engineering, Warehousing and Power BI integration
Capability to influence senior stakeholders, programme sponsors and project boards
Ability to communicate technical decisions to non-technical executives and secure agreement on technical direction
Deep knowledge of the Azure data stack (Azure SQL Server, CosmosDB, Azure Data Factory, Purview, Synapse, Event Hub, Azure Databricks/Fabric)
Extensive data modelling experience: both normalised relational models and de-normalised Star Schema/dimensional models
Excellent relational database design skills with expertise in diagnosing and optimising performance across SQL Server, PostgreSQL, and cloud databases
Proven track record with complex data migration projects (terabyte+ datasets, multiple legacy source systems, structures and unstructured data)
Proficiency with Parquet/Delta Lake or other modern data storage formats
Experience with streaming architectures using Kafka, Event Hubs, or Kinesis for real-time data processing
Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines
Experience processing and managing unstructured data types (text, images, logs, sensor data)
Understanding of Lambda and Kappa architectural patterns and when to apply each
Deep knowledge of Fabric architecture, governance, OneLake, Real-Time Intelligence, Data Engineering, Warehousing and Power BI integration
Capability to influence senior stakeholders, programme sponsors and project boards
Ability to communicate technical decisions to non-technical executives and secure agreement on technical direction
Deep knowledge of the Azure data stack (Azure SQL Server, CosmosDB, Azure Data Factory, Purview, Synapse, Event Hub, Azure Databricks/Fabric)
Extensive data modelling experience: both normalised relational models and de-normalised Star Schema/dimensional models
Excellent relational database design skills with expertise in diagnosing and optimising performance across SQL Server, PostgreSQL, and cloud databases
Proven track record with complex data migration projects (terabyte+ datasets, multiple legacy source systems, structures and unstructured data)
Proficiency with Parquet/Delta Lake or other modern data storage formats
Experience with streaming architectures using Kafka, Event Hubs, or Kinesis for real-time data processing
Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines
Experience processing and managing unstructured data types (text, images, logs, sensor data)
Understanding of Lambda and Kappa architectural patterns and when to apply each
Deep knowledge of Fabric architecture, governance, OneLake, Real-Time Intelligence, Data Engineering, Warehousing and Power BI integration
Capability to influence senior stakeholders, programme sponsors and project boards
Ability to communicate technical decisions to non-technical executives and secure agreement on technical direction
Deep knowledge of the Azure data stack (Azure SQL Server, CosmosDB, Azure Data Factory, Purview, Synapse, Event Hub, Azure Databricks/Fabric)
Extensive data modelling experience: both normalised relational models and de-normalised Star Schema/dimensional models
Excellent relational database design skills with expertise in diagnosing and optimising performance across SQL Server, PostgreSQL, and cloud databases
Proven track record with complex data migration projects (terabyte+ datasets, multiple legacy source systems, structures and unstructured data)
Proficiency with Parquet/Delta Lake or other modern data storage formats
Experience with streaming architectures using Kafka, Event Hubs, or Kinesis for real-time data processing
Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines
Experience processing and managing unstructured data types (text, images, logs, sensor data)
Understanding of Lambda and Kappa architectural patterns and when to apply each
Deep knowledge of Fabric architecture, governance, OneLake, Real-Time Intelligence, Data Engineering, Warehousing and Power BI integration
Capability to influence senior stakeholders, programme sponsors and project boards
Ability to communicate technical decisions to non-technical executives and secure agreement on technical direction
Deep knowledge of the Azure data stack (Azure SQL Server, CosmosDB, Azure Data Factory, Purview, Synapse, Event Hub, Azure Databricks/Fabric)
Extensive data modelling experience: both normalised relational models and de-normalised Star Schema/dimensional models
Excellent relational database design skills with expertise in diagnosing and optimising performance across SQL Server, PostgreSQL, and cloud databases
Proven track record with complex data migration projects (terabyte+ datasets, multiple legacy source systems, structures and unstructured data)
Proficiency with Parquet/Delta Lake or other modern data storage formats
Experience with streaming architectures using Kafka, Event Hubs, or Kinesis for real-time data processing
Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines
Experience processing and managing unstructured data types (text, images, logs, sensor data)
Understanding of Lambda and Kappa architectural patterns and when to apply each
Deep knowledge of Fabric architecture, governance, OneLake, Real-Time Intelligence, Data Engineering, Warehousing and Power BI integration
Capability to influence senior stakeholders, programme sponsors and project boards
Ability to communicate technical decisions to non-technical executives and secure agreement on technical direction
Deep knowledge of the Azure data stack (Azure SQL Server, CosmosDB, Azure Data Factory, Purview, Synapse, Event Hub, Azure Databricks/Fabric)
Extensive data modelling experience: both normalised relational models and de-normalised Star Schema/dimensional models
Excellent relational database design skills with expertise in diagnosing and optimising performance across SQL Server, PostgreSQL, and cloud databases
Proven track record with complex data migration projects (terabyte+ datasets, multiple legacy source systems, structures and unstructured data)
Proficiency with Parquet/Delta Lake or other modern data storage formats
Experience with streaming architectures using Kafka, Event Hubs, or Kinesis for real-time data processing
Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines
Experience processing and managing unstructured data types (text, images, logs, sensor data)
Understanding of Lambda and Kappa architectural patterns and when to apply each
Deep knowledge of Fabric architecture, governance, OneLake, Real-Time Intelligence, Data Engineering, Warehousing and Power BI integration
Capability to influence senior stakeholders, programme sponsors and project boards
Ability to communicate technical decisions to non-technical executives and secure agreement on technical direction

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