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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Solution Architect - **Company:** CAPGEMINI - **Location:** London, UK (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Audit Trail, Microsoft Azure, Big Data, Cloud Computing, Data Architecture, Data Validation, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Migration, Data Security, Data Warehousing, DevOps, Infrastructure as a Service (IaaS), Machine Learning, Microsoft SQL Server, SQL Azure, Platform as a Service (PAAS), Cloud Services, Azure Machine Learning, Azure Data Lake, Search Technologies, Cloud Platform System, Azure Data Factory, Apache Spark, SC Clearance, Build Management, Data Lakes, Data Analytics, Data Management, Machine Learning Operations, Data Pipelines, Legacy Systems, Databricks - **Published:** September 10, 2026 - **Apply:** https://www.collegerecruiter.com/job/2860991142-data-solution-architect ## About the Role As a senior architect, you'll also shape solutions and proposals alongside our sales and delivery teams, acting as the technical authority who turns client goals into deliverable, well-costed designs. Experience in public sector or other regulated industries is especially valued., To be appointed to this role, you must be eligible to obtain UK Security Check (SC) clearance. To obtain SC clearance, you must have resided continuously in the United Kingdom for the last 5 years, along with other criteria. Throughout the recruitment process you'll be asked about your security clearance eligibility, including country of residence and nationality. Some posts are restricted to sole UK Nationals for security reasons, so you may be asked about your citizenship., * Minimum 7+ years of experience as a Data Architect with experience in designing, developing and implementing cloud data solutions * Proven expertise in data platforms with a strong understanding of data warehousing concepts and practices. * Excellent problem-solving and analytical skills and strong communication and teamwork skills. * Design, Monitor and optimise data pipelines and infrastructure: Analyse performance metrics, identify bottlenecks, and implement optimisations for efficiency and scalability. * Design and oversee the delivery of secure data warehouses and data lakehouses: Implement data models, data quality checks, and governance practices to ensure reliable and accurate data. * Collaborate with cross-functional teams: Work closely with business analysts, data scientists, and DevOps engineers to ensure successful data platform implementations. * Stay ahead of the curve: Continuously learn and adapt to the evolving landscape of big data technologies and best practices * Relevant Architecture certifications from leading cloud platform providers * Ideally a background in Public Sector or other regulated industries Azure Working on Microsoft Azure PaaS and IaaS, specifically: App Services, Azure SQL Database, SQL Server, Storage, Synapse Analytics, Purview, Databricks, Azure data Factory, Azure data lake & Fabric. Understand which Azure data focused components to use for which purpose. Microsoft certified architect, * Design and build high-performance data platforms: Utilize Databricks and Apache Spark to extract, transform, and load data into Azure Data Lake Storage and other Azure services. * Ability to Design, Build and deploy AI/ML models: Integrate Machine Learning into data pipelines, leverage Databricks ML and Azure ML to develop predictive models and drive business insights. * Be a Databricks champion or have some Databricks certifications, * Work hands-on with AWS services such as Redshift, Glue, Lake Formation, SageMaker, Athena, and more * Strong hands-on expertise with AWS services (e.g. Redshift, Glue, Lake Formation, SageMaker). * AWS Certified Architect ## Description As a senior Data Solution Architect with an Azure and Databricks focus, you'll design the secure, scalable data platforms that our clients' analytics, AI and agentic systems run on. You'll own architecture from vision through to delivery: lakehouse and data-warehouse design, governance and trust, and increasingly the AI-native patterns (retrieval, vector search, agent orchestration) that let AI systems use enterprise data safely., As a Solution Architect with an Azure and Databrick focus, you will be an integral part of our team dedicated to building scalable and secure data platforms. You will leverage your expertise in Databricks, Apache Spark, and Azure to design, develop, and implement data warehouses, data lakehouses, and AI/ML models that fuel our data-driven operations., * Lead data platform architecture. Own the design and implementation of cloud-native data platforms, and drive modernisation strategies that move legacy systems to scalable, cloud-native solutions. * Design lakehouse architectures. Unify data lakes and warehouses to support advanced analytics, ML and GenAI workloads. * Define AI-native and agentic reference architectures. Design retrieval and RAG platforms, embeddings and vector search, feature and model serving, and patterns for exposing governed data to AI agents (for example through the Model Context Protocol), with the guardrails and human oversight that non-deterministic systems require. * Own data governance and trust. Establish lineage, access control, data quality and auditability using tools such as Unity Catalog and Microsoft Purview, aligned to responsible-AI expectations and emerging regulation (for example the EU AI Act and the UK's approach). In regulated and public sector work, this is a core part of the value, not an afterthought. * Provide technical pre-sales leadership. Shape solution direction, proposals, costing and estimates, and act as the technical liaison between clients, sales and delivery teams through to contracting. (This is solution shaping and technical authority, not a revenue-target sales role). * Set standards and optimise. Define reusable patterns, review designs against the architectural blueprint, and monitor and tune performance, cost and scalability across platforms. * Mentor and collaborate. Work closely with data engineers, data scientists, platform engineers and business analysts, growing capability and keeping solutions aligned to the overall architecture. * Stay ahead of the curve. Track the fast-moving data and AI landscape and bring credible, pragmatic recommendations. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Hacking MSSQL on Cloud. All of them. 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