Data Architect

The Data Architect within the Data AI Practice is responsible for the successful technical delivery of data and AI solutions, to time, budget and quality. The role will provide specialist technical knowledge to both bids and delivery projects, ensuring the data and technical architecture supports the customer and project needs. The role will lead the data engineering and science on a project and is responsible for the technical aspects of project delivery. The role requires the individual to lead and direct the project engineering and analysis teams along with line management responsibilities. The individual will have a strong professional services ethos and is confident in, reviewing, coaching and challenging others to drive up and increase the professionalism, client satisfaction, quality and profitability of the services delivered across the Sector. The role will be responsible for the technical aspects of project delivery and working alongside the project manager will focus on ensuring the technical quality within the project time and budget. The role will work with the other leads within the practice to design and deliver end to end data and AI solutions leveraging data in novel ways. Responsibilities: Successful technical delivery of data and AI solutions, ensuring they meet time, budget, and quality requirements. Provide specialist technical knowledge for bids and delivery projects. Direct data engineering and data science on projects. Lead and direct project engineering teams and manage the line management structure. Innovate with technology and data to drive better customer and business outcomes. Architect advanced solutions using simulation, predictive analytics, and artificial intelligence. Consult on data strategy and governance. Develop Data AI platform offerings, repeatable technology blueprints, and capability. What We're Looking For: Propose optimal data solutions and lead the design and creation of design artefacts. A solid team player who can nurture and develop a high-performing team. Collaborate with technical leads to maintain the right technical skills and capabilities. Ensure consistent ways of working following best practices and adherence to technical principles, standards, and frameworks. Lead teams and support team members and junior colleagues. Focus on delivery excellence to ensure projects succeed against time, budget, and quality. Passionate about technology and innovation. Required Skills: Proven record in enterprise and solution data architecture, including The Open Group Architecture Framework (TOGAF). Expertise in data modelling, manipulation, transformation, integration, warehousing, eventing, analytics, and presentation tools. In-depth knowledge of data lake, data lake house, data fabric and warehousing technologies. Experience delivering data quality and pipeline solutions. Familiarity with technical design standards and core technical principles. Ability to act as a client-facing trusted-advisor consultant. Knowledge of data and artificial intelligence standards such as GDPR, Information Security, and ethical AI. Experience with data obfuscation and the generation of synthetic data. Technical Skills: Data integration and pipeline development tools (e.g., MS Fabric, Azure Synapse, SAS DI Studio, Talend, IBM Datastage, AWS Glue). Core data integration languages (e.g., SQL, Python). Data lake supporting technologies (e.g., Azure Data Lake Gen 2, Hadoop, AWS S3, MS ADLS, Spark). Database/warehousing technologies (e.g., Oracle, SAP, Teradata, Snowflake). Data cataloguing and metadata management tools (e.g., MS Purview, Collibra Data Catalog, AWS Glue Data Catalog, Atlan Data Discovery Catalog) Data quality tools (e.g., Informatica IDQ, Talend Studio for DQ). AI and Machine Learning tools (e.g., Azure AI Platform, AWS Sagemaker). Cloud native delivery using the Microsoft Azure Cloud.