Data Architect (Machine Learning)

Location: one day a week on site in London
Security Clearance: The Data Architect will have the following responsibilities:
Collaborate with business and technology stakeholders to translate business problems into scalable data architecture solutions.
Design, document, and maintain enterprise and solution-level data architectures across multiple platforms and domains.
Define and enforce data standards, principles, and governance frameworks to ensure consistency and quality.
Develop conceptual, logical, and physical data models aligned with business needs and organisational strategy.
Select appropriate data storage, integration, and processing technologies for each projects context.
Guide the design and implementation of data platforms using cloud and hybrid environments (e.g. Azure, AWS).
Oversee the design of data pipelines, APIs, and services to ensure efficient data flow and interoperability.
Collaborate with Data Engineers and Developers to ensure alignment between architectural design and technical implementation.
Ensure compliance with security, privacy, and data protection requirements.
Govern architectural decisions and promote adherence to enterprise data standards.
Identify risks and dependencies in data delivery and develop mitigation strategies.
Contribute to data strategies, roadmaps, and vision for data enablement.
Work within agile delivery frameworks, contributing to planning, retrospectives, and sprint goals.
Collaborate with cross-functional teams, including Product Managers, Business Analysts, Data Governance and security experts.


Proven experience designing and implementing modern data architectures in cloud environments.
Strong understanding of data modelling (conceptual, logical, and physical), including relational, dimensional, and NoSQL approaches.
Expertise in data integration, ETL/ELT, and data pipeline design.
Hands-on experience with data lakehouse, warehouse, and streaming data architectures.
Working knowledge of SQL, Python, and relevant data engineering frameworks (e.g. Experience designing data platforms leveraging PaaS and SaaS solutions.
Solid understanding of information governance, metadata management, and master data management principles.
Experience leading data design across full project lifecycles (Discovery, Alpha, Beta, Live).
Due to the nature of the work and the sensitive data involved, Security Clearance (SC) is required for this role. Applicants must meet the UK government's security clearance requirements and be able to work within a secure environment.


Experience working on high-volume or high-performance data systems
Exposure to real-time data processing, IoT, or machine learning pipelines.
Knowledge of modern data mesh or data fabric principles.
Knowledge of government or public sector digital standards and GDS practices.
Experience in agile and DevOps delivery environments.
Certification in a major cloud platform (Azure Solutions Architect, AWS Certified Data Analytics, etc.).
Knowledge of data engineering best practices and testing frameworks.
Contribution to open-source projects, research publications, or professional communities.