> Markdown version of [/jobs/ext/2041624-lead-data-architect](https://www.wearedevelopers.com/jobs/ext/2041624-lead-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). --- # Lead Data Architect - **Company:** LA International Computer Consultants - **Location:** London, UK (Remote available) - **Experience:** Expert - **Salary:** £130,000.0 - £150,800.0 - **Contract:** Temporary contract - **Skills:** Application Frameworks, Architectural Patterns, Big Data, Data Architecture, Data Governance, Data Infrastructure, Interoperability, Metadata, Domain Driven Design, Databricks - **Published:** August 13, 2026 - **Apply:** https://www.careerboard.com/pt/en/find-jobs-in-United-Kingdom/-AA912F52D2E9228193/ ## About the Role Strong experience leading enterprise data architecture and large-scale data transformation programs. - Deep understanding of Data Mesh, data products, domain-driven design, federated governance, data product life cycle management, and data-as-a-product principles. - Experience defining enterprise, domain, conceptual, logical, and physical data architectures. - Strong understanding of end-to-end data life cycle management. - Experience designing reusable data platform capabilities, engineering frameworks, architecture patterns, and delivery accelerators. - Ability to translate business strategy and domain requirements into pragmatic architecture and executable delivery plans. - Experience leading proofs of concept, technology evaluations, architecture reviews, and executive-level presentations. - Strong understanding of modern data platforms like databricks - Proven ability to lead multidisciplinary teams involving domain experts, business analysts, data modelers, platform architects, governance specialists, and data engineers. - Strong stakeholder management, facilitation, technical leadership, communication, and decision-making skills. ## Description Define and govern the overall data architecture, Data Mesh implementation approach, and data product delivery principles for the program. - Act as the overall program technology lead, ensuring alignment across business priorities, domain architecture, data modelling, platform capabilities, engineering, governance, and consumption requirements. - Work with different levels of client management to support strategy definition, delivery planning, implementation oversight, architectural decision-making, and frictionless delivery of data products. - Collaborate with domain consultants and business stakeholders to identify, define, decompose, and prioritize data products. - Establish architecture standards and decision frameworks for data product boundaries, domain ownership, interoperability, sharing, discoverability, quality, security, and life cycle management. - Lead the design of reusable frameworks, foundational capabilities, templates, and components that accelerate the end-to-end data product life cycle. - Lead proofs of concept, proofs of technology, architecture assessments, and evaluation exercises, and present findings and recommendations to client stakeholders. - Work with engineering teams to ensure optimal data product design, including ingestion, transformation, storage, orchestration, quality, security, observability, and consumption patterns. - Review solution designs, resolve cross-domain architecture concerns, manage technical dependencies, and govern architecture exceptions. - Ensure alignment between data product delivery and enterprise data governance, metadata, lineage, access control, data quality, and certification requirements. - Provide technical direction to architects, data modelers, analysts, and engineers, and facilitate architecture and design reviews across delivery teams. - Identify architectural risks and delivery constraints, define mitigation actions, and communicate technology decisions and implications to program leadership. - Drive consistency and reuse across domains while allowing appropriate autonomy for domain-specific implementation decisions. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) - [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) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - 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