Senior Data Architect

Key Responsibilities: Define data engineering strategies and technical roadmaps that align with client requirements and wider business objectives. Lead the architecture and implementation of large-scale data lakehouse and warehouse solutions, with strong experience across Databricks. Design and build scalable data platforms across cloud environments, including AWS and Azure, as well as hybrid and on-premises infrastructure. Oversee the development of data pipelines covering batch and real-time ingestion, streaming, ETL/ELT and data transformation. Ensure data platforms are built with the right levels of security, governance, compliance and data quality. Take ownership of complex engineering challenges, making key architectural decisions and identifying potential risks across delivery. Drive platform performance, scalability and cost optimisation, ensuring solutions are built for long-term use. Stay up to date with emerging data technologies and introduce new approaches where they can add value to client solutions. Provide technical leadership to engineering teams, including mentoring engineers, reviewing architecture and code, and supporting implementation. Work directly with clients during technical discovery, helping define requirements and translate them into technical solutions. Support pre-sales activity, including technical proposals, RFP responses, pricing, presentations, demonstrations and proof of concepts. Produce technical designs and architecture blueprints, recommending the right tools, frameworks and engineering approaches for each project.

Required Experience & Qualifications: Bachelor's or Master's degree in Computer Science, Engineering or a related technical discipline.5+ years' experience across data engineering and architecture, ideally working on large-scale cloud data projects.4+ years' experience in client-facing roles, ideally within a consultancy or professional services environment. Strong track record designing and delivering modern data platforms, including data lakehouses, warehouses and complex data pipelines. Expert-level Databricks and Apache Spark experience (essential).Strong cloud experience across AWS and/or Azure. Experience working across data ingestion, transformation, storage and real-time processing architectures. Previous involvement in technical pre-sales, including solution design, proof of concepts, client presentations and engagement pricing. Confident communicating with both technical teams and senior business stakeholders, with the ability to influence decisions and build strong client relationships.