Hybrid Data Architect – Scientific Compute

at Ellison Institute of Technology Oxford

• Job title: Data Architect – Scientific Compute
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: No Education Requirement
• Tech skills: Cloud
• Location requirements: Hybrid, Oxford, United Kingdom

About the role

• Data Architect needed to define and evolve data architecture supporting scientific compute at EIT. Collaborate and lead in large-scale research environments for transformative scientific challenges.

Responsibilities

• **Your Responsibilities:**
• __Data & Storage Architecture Collaboration__
• Collaborate with research group technical leadership to define and continuously evolve the institute-wide data and storage architecture supporting large-scale scientific compute.
• Define target-state data architectures for scientific data that enable EIT’s institutes to do their best work, balancing standardisation, flexibility, scalability, performance, resilience, and security across heterogeneous scientific data workloads.
• Work hand-in-glove with other data teams within the Institute including Data Engineering (within AI and Robotics) and Enterprise Applications to ensure strategic and operational alignment across disciplines.
• Translate organisational strategy and scientific priorities into coherent data architecture roadmaps for scientific compute.
• ____
• __Standards, Schemas & Consistency__
• Define and own institute-wide data standards that are utilised by our scientists and developers, including schemas, metadata models, naming conventions, and configuration baselines.
• Ensure that consistent standards, schemas, and configuration settings are used across all scientific programmes, wherever appropriate.
• Balance standardisation with scientific flexibility, providing clear, governed patterns for extension rather than divergence.
• ____
• __Large-Scale Data Integration & AI Enablement__
• Architect approaches for integrating data across scientific programmes into unified, high-quality datasets.
• Enable the creation of very large datasets suitable for advanced analytics, machine learning, and large language model training.
• Work closely with scientific compute, AI, and platform teams to ensure data architectures are optimised for large-scale downstream consumption.
• ____
• __Data Governance, Classification & Compliance__
• Be accountable for aligning data and storage operational standards with data classification models defined by the Institute’s Data Protection Officer (DPO) and other data specialists.
• Translate governance, privacy, and security requirements into clear, practical architectural and operational standards.
• Ensure data is handled appropriately throughout its lifecycle, including ingestion, storage, access, sharing, retention, and deletion.
• ____
• __Collaboration & Influence__
• Act as a trusted partner to scientific compute leaders across programmes, engaging deeply with their requirements, constraints, and research priorities.
• Lead through influence rather than mandate, collectively defining shared schemas and standards that programmes commit to and adopt.
• Support programmes with the operationalisation of agreed standards, ensuring they are embedded into delivery pipelines and day-to-day practices.
• ____
• __Operationalisation & Enablement__
• Ensure data architecture standards move beyond definition into implementation and sustained operation.
• Provide guidance, reference architectures, and hands-on support to programme teams adopting shared data and storage standards.
• Work alongside platform, DevOps, and operations teams to embed standards into tooling, automation, and operational processes.

Requirements

• **Essential Skills, Qualifications & Experience:**
• Extensive, demonstrable experience as a Data Architect operating at enterprise or institute-wide scale.
• Proven experience designing data and storage architectures for large-scale scientific, research, or compute-intensive environments.
• Strong experience defining and governing data standards, schemas, metadata models, and configuration baselines across multiple teams.
• Deep understanding of data governance, classification, privacy, and compliance in complex organisations.
• Demonstrated ability to integrate data across domains to support advanced analytics and AI/ML use cases.
• Significant experience influencing senior technical, scientific, and data stakeholders in matrixed organisations.
• **Desirable Knowledge, Skills and Experience:**
• Background in scientific research, HPC, AI/ML platforms, or data-intensive research environments.
• Experience supporting large-scale AI or LLM training pipelines.
• Experience modernising or standardising data architectures across federated or decentralised research teams.
• Experience operating within large-scale cloud-based data platforms.

Benefits

• **Our Benefits:**
• Competitive salary + travel allowance + bonus
• Enhanced holiday + options to buy additional days
• Pension
• Life Assurance
• Income Protection
• Private Medical Insurance
• Hospital Cash Plan
• Therapy Services
• Perk Box
• Electric Car Scheme
• Childcare benefit