> Markdown version of [/jobs/ext/1462015-principal-enterprise-data-architect](https://www.wearedevelopers.com/jobs/ext/1462015-principal-enterprise-data-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Enterprise Data Architect - **Company:** Roche - **Location:** Welwyn, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Query Performance, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Architectural Patterns, Microsoft Azure, Cloud Computing, Databases, Data Architecture, Data Integration, Extract Transform Load (ETL), Data Security, Data Sharing, Data Structures, Data Systems, Graph Database, Machine Learning, Meta-Data Management, NoSQL, Reference Data, Cloud Services, Semantic Web, Data Streaming, Technical Data Management Systems, Enterprise Data Management, Snowflake, Database Optimization, Multi-Cloud, Togaf, Data Lakes, Integration Frameworks, Data Management - **Published:** July 28, 2026 - **Apply:** https://dejobs.org/x/x/62CD0C3286684E8FA5C2BB8027E6F181/job/ ## About the Role * Extensive Experience: Leading the development, continuous improvement, and execution of complex enterprise data architectures and data modeling initiatives in a large-scale corporate environment. * Proven Track Record: Architecting, deploying, and optimizing enterprise data warehouses, data lakes, and transactional databases. * Framework Mastery: Demonstrated experience implementing data frameworks (e.g., TOGAF, DAMA-DMBOK) and modern paradigms like Data Mesh. * Project Leadership: Proven history of leading high-impact migration, modernization, or master data management (MDM) projects that shape overarching corporate data policies. Technical & Business Skills * Data Architect * Expert proficiency in cloud data platforms (e.g. Snowflake, AWS, Azure). * Deep expertise in data integration patterns (ETL/ELT, API-led connectivity). * Strong capability to design distributed, highly available, and secure data pipelines. * Information Architect * Deep expertise in metadata management, master data management (MDM), and reference data management. * Proven ability to construct enterprise taxonomies, ontologies, data lineages, and business glossaries. * Strong understanding of semantic web technologies (RDF, OWL, Knowledge Graphs). * Data Modeler * Expert proficiency in industry-standard data modeling tools. * Mastery of multiple modeling paradigms, e.g. Relational, Dimensional, and NoSQL/Document modeling. * Advanced knowledge of database optimization, indexing strategies, and query performance tuning., * Exceptional Stakeholder Management: Ability to act as a key advisor and translate complex technical architecture into clear business outcomes for non-technical senior leadership. * Strong Leadership: Capabilities to guide, direct, and oversee cross-functional engineering and product teams. * Strategic Alignment: Ability to drive cross-functional initiatives aimed at enhancing data trust, discoverability, and accessibility while ensuring strict alignment with overarching organizational business strategies. ## Description The Principal Data Architect, Information Architect, and Lead Data Modeler drives the strategic vision, structural design, and semantic definition of the organization's enterprise data ecosystem. This role bridges the gap between high-level business strategy and technical execution, leading the design of scalable data architectures, comprehensive information blueprints, and robust enterprise data models. As a Principal Data Architect, you will champion data democratization, mentor junior architects and modelers, drive cross-functional alignment on data standards, and act as a primary technical advisor to senior leadership on modernizing our data landscape for analytics, AI, and operational excellence., Data Architecture: Leads the definition and deployment of target-state enterprise data architectures, cloud data platforms, and data integration strategies. * Information Architecture: Establishes the enterprise-wide business glossary, conceptual data blueprints, and taxonomy/ontology frameworks to ensure a unified understanding of data across the business. * Data Modeling: Oversees the creation and maintenance of enterprise conceptual, logical and physical data models * Mentorship: Oversees and mentors junior data architects, modelers, and engineers within the team. Accountability / Problem Solving * Addresses highly complex structural and data integration issues across legacy, hybrid, and multi-cloud environments. * Resolves semantic ambiguity and structural conflicts across diverse business units to create a cohesive, single source of truth. * Ensures data structures are optimized for performance, scalability, security, and cost-efficiency. Stakeholder Management * Liaises directly with senior leadership, product owners, and business analysts to translate business strategy into technical data requirements. * Guides and directs engineering, application, and analytics teams on structural compliance, modeling standards, and architectural patterns. Impact / Strategy * Leads high-impact infrastructure and modeling projects that significantly shape the organization's long-term data capabilities. * Develops long-term strategies for data minimization, retention-by-design, and decoupled data sharing. Complexity / (Product Size) * Manages enterprise-level data models and architecture systems, and real-time streaming pipelines. * Designs and implements advanced, reusable data patterns that scale frictionlessly across the organization. Business / Technical Ability * Acts as an expert in modern data technologies, cloud infrastructure, and advanced data modeling methodologies. * Demonstrates a deep understanding of how data structures impact downstream AI/ML, advanced analytics, and business intelligence. ## Related Videos - [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) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [NoSQL Data Modeling for Front-end Developers](https://www.wearedevelopers.com/videos/297-nosql-data-modeling-for-front-end-developers) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers)