Data Architect

Job Title: Data Architect Key Responsibilities • Design, define, and govern the enterprise data architecture, including data lakes, data warehouses, data marts, and operational data stores (ODS), contributing to the definition and evolution of Aptia’s data strategy. • Establish and maintain data architecture standards and governance, covering data ingestion, orchestration, transformation, data quality, security, and access controls. • Own and define the end to end data architecture for new initiatives, combining hands on solution design with active delivery support to ensure architectural intent and business benefits are fully realised. • Collaborate closely with delivery teams to guide design decisions, resolve architectural trade offs, and support implementation through to production. • Contribute to Architecture Review Boards (ARB) and other technical governance forums, providing expert input and assurance. • Provide technical leadership and mentoring to architects and engineering team members, promoting best practices and architectural consistency. • Ensure alignment with enterprise, security, and regulatory architecture standards and policies. Competency • 10+ years of experience in IT, with at least 4+ years as a Data Architect or Principal Data Engineer, ideally within the UK financial services or pensions administration sector. • Proven experience designing and delivering large scale, cloud based data platforms (AWS, Azure, or GCP) using Databricks. • Strong knowledge of data modelling techniques, with expert proficiency in both relational and NoSQL databases. • Experience working with large, complex application and data landscapes. • Strong communication skills, with the ability to explain architectural concepts clearly to non technical stakeholders. • Ability to collaborate, influence, and negotiate effectively to turn business goals into a clear, actionable implementation roadmap. • Strong problem solving mindset, with a commitment to continuous learning and adaptability across emerging technologies (cloud, GenAI, streaming). Education • Bachelor’s or Master’s degree in Computer Science, Data Science, or a related technical field Preferred Qualifications • Experience in a product-centric or SaaS company. • Familiarity with MLOps principles and the data architecture required to support machine learning models and GenAI applications. • Relevant professional cloud certifications (e.g., AWS Certified Data Analytics, Azure Data Engineer Associate).