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Data Architect
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Data Architect - Perm Role
Salary: £94K base + benefits
Hybrid: 3 days a week travel to the office in Central London
We are hiring a Data Architect to define, design, and evolve enterprise data architecture across modern cloud and lakehouse platforms. You will translate business, analytics, and AI requirements into robust data models, integration patterns, platform standards, and governance controls that create trusted, reusable data assets. This is a Data Architect who is a Databricks engineer by trade. This is a senior technical leadership role with architecture ownership scope: you will shape data architecture principles, guide design reviews, collaborate with engineering and analytics teams, and make practical trade-offs across data modelling, integration, governance, performance, security, cost, and operational resilience.
Duties & Responsibilities
- Lead the design and evolution of enterprise data architecture that supports business intelligence, analytics, automation, and AI use cases
- Develop conceptual, logical, and physical data models for core business domains, data products, reporting layers, and analytical platforms
- Define data integration patterns, data flow designs, and reusable architecture standards for batch, streaming, API-based, and event-driven data movement
- Establish data governance, data quality, metadata, lineage, security, and privacy standards in partnership with engineering, governance, and business stakeholders
- Collaborate with data engineers, analytics engineers, product owners, and business stakeholders to translate requirements into scalable, maintainable, and secure data solutions
- Provide technical leadership through architecture reviews, design documentation, data standards, reference patterns, and guidance for delivery teams
- Strong SQL, data modelling, and data platform skills, with practical experience designing schemas, semantic layers, dimensional models, and enterprise data structures
- Hands-on experience with modern data platforms such as Databricks, Microsoft Fabric, Azure Data Lake, Azure Synapse, Snowflake, or comparable cloud data technologies
- Experience designing lakehouse, data warehouse, data mart, and data product architectures that support trusted analytics and operational reporting
- Ability to define metadata, lineage, master data, reference data, and data quality approaches that improve trust, discoverability, and reuse of data assets
- Experience using Databricks, Spark, and lakehouse concepts for scalable data storage, transformation, governance, and analytical consumption
- Familiarity with Microsoft Fabric, Azure Data Factory, Azure Synapse, Azure Purview, or comparable cloud-based data architecture and governance services
- Experience with engineering practices including, Git, automated testing, CI/CD, infrastructure-as-code, documentation, and operational monitoring for data platforms
- Ability to use AI-assisted development and documentation tools responsibly to improve architecture design, productivity, and knowledge sharing
- Proven track record delivering data architecture, data platform, or enterprise data management solutions in production environments
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Certifications (Nice to Have)
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- Degree in Computer Science, Information Systems, Data Engineering, Software Engineering, Mathematics, or equivalent practical experience
- Relevant Microsoft Azure certifications or exams such as DP-900, DP-203, DP-600, AZ-305 or AI-102
- Relevant Databricks certifications such as Data Engineer Associate, Data Engineer Professional, or Lakehouse Fundamentals
- Any recognised certifications in data architecture, data governance, cloud architecture, data management, or enterprise architecture are advantageous
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