Data Architect jobs in United Kingdom

With around 550,000 employees in 55,000 client locations in 30+ countries Compass Group has a broad and diverse footprint. The decentralised operating model is considered a competitive advantage enabling a client‑oriented culture with innovation at the front line. This stimulates creativity and to support this the group builds and aligns appropriate operating frameworks, solutions and leads on best practice sharing. Our Group leadership team is motivated to create significant advantage using digital & Data solutions in both front and back of house, which leads to our desire to strengthen group‑wide technology and data capabilities across key strategic pillars to drive significant Growth & Performance commercial outcomes.

• Provide technology thought leadership in the design, engineering, and management of Compass Group Solutions’ data and AI architecture, ensuring alignment with business objectives and strategy.
• Define, implement and maintain methodologies, frameworks, and platforms for scalable, high‑quality, and reusable data and AI solutions.
• Lead the integration and operationalisation of advanced analytics and AI capabilities, ensuring solutions are robust, secure, and efficient.
• Evaluate and recommend emerging technologies, tools, and best practices to continually enhance Compass Group Solutions’ data and AI landscape.
• Collaborate with business stakeholders, product owners, and technology teams to translate business needs into effective data and AI solutions.
• Develop and enforce data governance, quality, security, and privacy standards across all data and AI initiatives.
• Architect solutions that integrate structured and unstructured data from multiple sources to enable advanced analytics and AI‑driven insights.
• Guide the end‑to‑end lifecycle of AI and analytics projects, from ideation and architecture through implementation and operationalisation.
• Provide technical leadership, mentorship, and knowledge sharing to data engineers, data scientists, and other team members.
• Develop and maintain documentation for architectural standards, processes, and procedures.
• Ensure compliance with regulatory requirements and internal policies regarding data and AI.
• Foster a culture of innovation, championing new ideas, approaches, and technologies within Compass Group Solutions.
• Engage with global and local teams to ensure effective and safe use of AI technologies across the business.

• Proven experience as a Data Architect, Analytics Architect, AI Architect, or similar role in a complex, enterprise environment.
• Deep expertise in data architecture, data modelling, data warehousing, and big data technologies.
• Strong understanding of AI/ML concepts, frameworks, and lifecycle management.
• Experience designing and implementing cloud‑based data and AI solutions (e.g., Azure, AWS, GCP).
• Experience with database technologies such as SQL, NoSQL, Oracle, Hadoop, or Databricks.
• Experience with Microsoft Fabric.
• Proficiency with data integration, ETL, and data pipeline tools.
• Familiarity with data governance, security, and privacy best practices.
• Excellent communication and stakeholder management skills.
• Ability to translate business requirements into technical solutions.

• Strong programming skills (e.g., Python, SQL, Java) and experience with AI/ML libraries (e.g., TensorFlow, PyTorch, scikit‑learn).
• Ability in data science languages/tools such as R, SAS, or Excel.
• Understanding of entity‑relationship modelling, metadata systems, and data quality tools and techniques.
• Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP), real‑time data distribution (Kafka, Dataflow), and modern data warehouse tools (Snowflake, Databricks).
• Skilled in selecting and architecting AI frameworks (e.g., TensorFlow, PyTorch, Hugging Face), cloud platforms (Azure, AWS, Gcp), and orchestration tools (Docker, Kubernetes) for scalable enterprise AI solutions.
• Ability to apply AI application testing techniques (e.g., pairwise testing, A/B testing, back‑to‑back testing) across operating system platforms.
• Familiarity with ModelOps, AI engineering practices, DevOps and MLOps (e.g., CI/CD pipelines).

• Ability to think strategically and link architectural decisions and recommendations to business needs and client culture.
• Ability to guide solution design and architecture to meet business needs.
• Advanced understanding of system integration architecture.
• Strong documentation skills with the ability to produce diagrams, demos, and technical artifacts that make AI architectures comprehensible and actionable.
• Strong analytical and problem‑solving skills.
• Ability to synthesize and clearly communicate large volumes of complex information to senior managers with various technical understandings.
• Influencing and networking skills; ability to collaborate and excel in complex, cross‑functional teams involving data scientists, business analysts, and stakeholders.
• Excellent written and verbal communication skills; ability to communicate complex AI concepts to non‑technical audiences.