> Markdown version of [/jobs/ext/4555401-senior-data-architect](https://www.wearedevelopers.com/jobs/ext/4555401-senior-data-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Architect - **Company:** Tenth Revolution Group - **Location:** London, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, ARM Architecture, Cloud Computing, Data Architecture, Information Engineering, Data Governance, Dataspaces, Graph Database, Identity and Access Management, Cloud Services, Data Mesh, Feature Store, LangChain, Snowflake, Informatica Cloud, Electronic Medical Records, Generative AI, Agentic-AI, Data Strategy, Collibra, Amazon Bedrock, Data Management, Machine Learning Operations, Data Lakehouse, Graph RAG, Databricks - **Published:** November 4, 2026 - **Apply:** https://www.apply4u.co.uk/jobs/senior-data-architect/54955437 ## About the Role Technology Environment AWS (S3, EC2, IAM, EMR), Snowflake, Snowpark, Iceberg Tables, Cortex, Databricks, MLflow, Feature Stores, dbt Cloud/Core, Apache Airflow, Fivetran, SnapLogic, Collibra, Acceldata, Sinequa, Amazon Bedrock, LangChain, Agent Frameworks, Knowledge Graphs, and GraphRAG architectures. Required Experience 20+ years of experience within Data Architecture, Enterprise Architecture, Data Strategy, or related disciplines. Director or Senior Director-level experience within a consulting organisation or complex enterprise environment. Experience delivering enterprise transformation programmes. Deep expertise across cloud data platforms, governance, data management, AI, and modern data ecosystems. Strong experience designing AWS and Snowflake-based architectures. Experience implementing Data Mesh, Data Lakehouse, advanced data platforms, and Data Product operating models. Experience defining enterprise architecture standards, governance frameworks, and strategic roadmaps. Strong stakeholder engagement and advisory skills, including working with executive audiences. Consulting and client-facing experience within complex organisations. Industry Knowledge Experience within the Pharmaceutical or Life Sciences sector is highly desirable, including familiarity with: Research and Discovery Clinical Development Regulatory Affairs Manufacturing and Supply Chain Commercial Operations Post-Market Activities Ideal Profile The ideal candidate will be a strategic and technically credible Data Architecture professional who can work effectively across engineering, data science, business, and transformation functions. They will bring a practical approach to problem solving, strong communication skills, and the ability to translate complex technical requirements into business value while helping organisations modernise their data and AI capabilities. ## Description We are seeking an experienced Senior Data Architect with a strong consulting background to shape enterprise-wide Data and AI transformation initiatives. This role requires someone who can align technical architecture, data science, and business priorities to create scalable, future-ready data ecosystems. Working with senior stakeholders across technology and business functions, you will define target-state architectures, develop transformation roadmaps, and provide architectural expertise across cloud platforms, governance frameworks, data platforms, artificial intelligence, and Generative AI capabilities. Key Accountabilities Define and deliver enterprise Data and AI strategies aligned to organisational priorities. Design secure, scalable, and governed data platforms across cloud and hybrid environments. Architect modern Data Lakehouse, Data Mesh, Semantic Layer, and Knowledge Graph solutions. Establish data governance frameworks, standards, and operating models covering quality, lineage, security, and compliance. Enable the adoption of Data-as-a-Product principles and federated governance practices. Partner with stakeholders to develop technical roadmaps and transformation plans. Provide architectural direction across Data Engineering, Data Science, AI, and reporting teams. Advance innovation in areas such as AI readiness, automation, advanced insights, and Generative AI. Guide multidisciplinary teams and promote architecture best practices. Communicate complex technical concepts clearly to both technical and non-technical audiences.