As Data Architect, you design scalable, secure data solutions on Microsoft Azure for clients, shaping end-to-end data platforms amid ingestion, storage, transformation, governance and analytics. You’ll collaborate with clients, delivery teams and internal stakeholders to translate business needs into robust architectures aligned with goals, performance, security and cost considerations. This hybrid role in Manchester or London offers the chance to lead architectural design, guidance, and governance across data layers and lakehouse/warehouse implementations.
Responsibilities
Design end-to-end data solutions across ingestion, transformation, storage, modelling and consumption
Understand client goals, reporting needs, data challenges and constraints
Produce architecture documentation, solution designs and data models
Create secure, scalable, resilient, and maintainable data platforms
Define patterns for data integration, transformation, storage and analytics
Support lakehouse, warehouse and reporting solutions using Azure services
Incorporate data quality, lineage, governance and security into designs
Collaborate with engineers and consultants; facilitate client and delivery workshops
Evaluate design options and contribute to best practices and reusable assets; mentor junior team members
Key requirements
Experience in data engineering, data solution design, or data architecture roles with strong Azure data services expertise
Strong understanding of end-to-end data architecture (ingestion, transformation, storage, modelling, reporting)
Experience with Azure data services such as Data Factory, Databricks, Synapse Analytics, Fabric, Data Lake Storage
Solid data modelling knowledge (logical, physical, dimensional, analytical)
Ability to produce architecture artefacts and technical documentation aligned to requirements
Customer-facing experience with effective stakeholder engagement
Knowledge of data quality, security, access control and governance; good communication and problem-solving skills
Self-sufficient yet collaborative; detail-oriented and outcome-focused
Experience with Fabric, lakehouse architectures and hands-on development using Python, SQL or Spark is advantageous
Familiarity with integration technologies; awareness of DevOps, IaC, Purview, Power BI, other cloud platforms and AI/ML use cases would be beneficial
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