As the Lead Enterprise Architect for Data & AI, you will be responsible for defining and driving an enterprise-wide data and information architecture strategy. Your role will ensure data platforms, governance frameworks, and information assets are fully aligned with the needs of business domains such as Commercial, Finance, Supply Chain, Product, and Regulatory. You will lead the design of a scalable, trusted, and connected data architecture that enables AI/ML, advanced analytics, digital transformation, and regulatory compliance. This is a critical leadership role in advancing the organization’s data-driven enterprise vision. Core Responsibilities of the Enterprise Architect Role: Bridge alignment between business and IT across a federated technology environment. Build strong stakeholder relationships with business and IT leaders. Visualize future-state architectures to influence long-term business planning. Operate across multiple delivery models, including product- and project-centric environments. Define the enterprise data architecture vision, target state, and guiding principles, aligned with business priorities and regulatory frameworks. Lead architecture for enterprise data platforms such as Azure Synapse, Databricks, Power BI, and Informatica. Establish enterprise-wide standards for master data, metadata, lineage, and data stewardship. Collaborate with business and domain architects to identify and support key data domains. Provide architectural oversight for major initiatives in data ingestion, transformation, and analytics. Define data access, privacy, quality, and lifecycle management policies at the enterprise level. Champion enterprise taxonomies, data product strategies, and federated governance. Stay informed on and assess innovations such as data mesh, lakehouse, and generative AI for enterprise applicability. federated data ownership and governance models. data lakehouse vs. warehouse) for enterprise-wide data needs. immediate business-driven data initiatives. Defining abstraction levels for enterprise data models and ontologies. Recommending scalable architectures for AI/ML workloads and real-time data streaming. Significant experience in enterprise architecture with a strong focus on data, information, or analytics. Proven hands-on expertise with data platforms such as Azure Data Lake, Synapse, Databricks, Power BI, etc. Deep knowledge of data governance, MDM, metadata management, and data quality frameworks. Understanding of data protection and privacy regulations (e.G., Track record of developing and executing enterprise data strategies at scale. Analytical and problem-solving mindset with a focus on long-term value creation. Experience with data governance tools like Collibra, Informatica Axon/EDC. Knowledge of advanced data architecture concepts (e.G., data mesh, data fabric, domain-oriented design). Familiarity with data science and AI/ML platforms and their integration into enterprise strategies. FMCG, finance, life sciences). Experience with enterprise-scale transformation initiatives. data, applications, security, integration); MBA or postgraduate diploma preferred. Employment type Full-time Job function Information Technology Sign in to set job alerts for “Data Architect” roles. Central Operations Enterprise Data Architect - SVP Senior Cloud and Data Solution Architect Senior Technology Architect-Cloud Data Mesh Enterprise Information Technology Architect Data Architect - AWS & Snowflake Expertise We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI. #
