OF1059 - Data & AI Engineering Resource Provision

Description

Terms and acronyms SFIA (Skills Framework for the Information Age) A global skills and competency framework for digital and IT professionals. Roles in this procurement are aligned to SFIA Levels 3–7, which define responsibility and autonomy. API (Application Programming Interface) A set of rules and protocols that allow different software applications to communicate with each other. APIs enable integration between systems. REST (Representational State Transfer) An architectural style for designing networked applications. REST APIs use HTTP methods for communication and are widely used for web services. OAuth2 An open standard for access delegation, commonly used for secure API authentication and authorisation. JWT (JSON Web Token) A compact, URL-safe means of representing claims securely between two parties, often used for authentication in APIs. Carbon Design System An open-source design system developed by IBM, providing reusable components and guidelines for creating consistent user interfaces. Cloud-native An approach to building and running applications that exploit the advantages of cloud computing delivery models, including scalability and resilience. CI/CD (Continuous Integration / Continuous Deployment) A set of practices for automating the integration and deployment of code changes, improving software delivery speed and quality. Observability The ability to measure and understand the internal state of a system based on the data it produces, such as logs, metrics, and traces. Logging Recording events and messages generated by software systems to support monitoring, troubleshooting, and auditing. Summary of the work: Ofqual requires specialist data and AI engineering resources to develop, optimise, and govern its data platforms and analytical capabilities. This will ensure that Ofqual’s data infrastructure is secure, scalable, and capable of delivering actionable insights while meeting regulatory and organisational objectives. The work addresses the need for flexible, expert capability to manage and leverage Ofqual’s data assets. Existing systems require enhancement to support advanced analytics and machine learning, and new solutions must be implemented to ensure ongoing compliance with data ethics and governance standards. The supplier will provide skilled resources across SFIA Levels 3 to 7 to design, build, and maintain data pipelines, analytical models, and governance frameworks that underpin critical business processes. They will also commit through the course of the contract to providing strategic challenge and support. Adopting modern DataOps and MLOps practices is also a key driver, improving reliability, scalability, efficiency, and resilience across data and machine learning workflows. The work focuses on data engineering and integration, AI and ML development and deployment, responsible AI and data ethics, governance and compliance, and visualisation and insight. By undertaking this work, Ofqual will be better able to harness data and AI technologies to improve operational efficiency, enhance regulatory oversight, and deliver better outcomes for stakeholders. Pricing model: Capped time and materials Confirm if you require a contracted out service or supply of resource: Contracted out service: the off-payroll rules do not apply Organisation the work is for: The Office of Qualifications and Examinations Regulation (Ofqual) Where you want the supplier to work: No specific location (for example they can work remotely) Latest start date: 2026-09-01 Expected contract length: 2-00-00 Expected contract structure: 1 Year initial period 1 Year extension period Estimated contract value (excl VAT): 99999 Budget details: £99,999 is for first year. Why the work is being done: Ofqual requires specialist data and AI engineering resources to develop, optimise, and govern its data platforms and analytical capabilities. This will ensure that Ofqual’s data infrastructure is secure, scalable, and capable of delivering actionable insights while meeting regulatory and organisational objectives. The work addresses the need for flexible, expert capability to manage and leverage Ofqual’s data assets. Existing systems require enhancement to support advanced analytics and machine learning, and new solutions must be implemented to ensure ongoing compliance with data ethics and governance standards. The supplier will provide skilled resources across SFIA Levels 3 to 7 to design, build, and maintain data pipelines, analytical models, and governance frameworks that underpin critical business processes. Adopting modern DataOps and MLOps practices is also a key driver, improving reliability, scalability, efficiency, and resilience across data and machine learning workflows. The work focuses on data engineering and integration, AI and ML development and deployment, responsible AI and data ethics, governance and compliance, and visualisation and insight. By undertaking this work, Ofqual will be better able to harness data and AI technologies to improve operational efficiency, enhance regulatory oversight, and deliver better outcomes for stakeholders. Problem to be solved: Ofqual needs flexible, specialist capability across SFIA Levels 3 to 7 to manage and leverage its growing data assets. Existing systems require enhancement to support advanced analytics and machine learning, and new solutions must be implemented to ensure compliance with data ethics and governance standards. Ofqual also needs to adopt modern DataOps and MLOps practices to improve reliability, scalability, efficiency, and resilience. The problem to be solved is to provide skilled resources who can: • Build and optimise ETL processes and data pipelines using Azure Data Factory and Databricks to deliver reliable and performant data flows. • Design, train, and deploy machine learning models that provide predictive insights to support decision-making. • Embed responsible AI and data ethics to ensure fairness, transparency, and accountability in AI solutions. • Implement automation, monitoring, and CI/CD pipelines for data and ML workflows to improve reliability and scalability. • Establish robust data governance aligned with GDPR and security standards to protect sensitive information and maintain trust. • Deliver clear, actionable insights through dashboards and reports using Power BI and other visualisation tools. Addressing this problem will enable secure, scalable data infrastructure and analytical capabilities that underpin critical business processes and support Ofqual’s regulatory objectives. Who the users are and what they need to do: As an internal business user, I need high‑quality data that is accurate, timely, and easy to access, So that I can carry out regulatory tasks efficiently and make informed decisions. As a compliance officer, I need confidence that all data processing, analytics, and AI development follows governance, security, and ethical standards, So that Ofqual meets statutory obligations and protects sensitive information. As a technical architect (data domain), I need data engineers, analytics engineers, and ML specialists who can build scalable and reliable data platforms, So that I can design solutions that align with Ofqual’s data strategy and support long‑term operational needs. As a product owner, I need data engineering and analytical work to deliver clear value and meet user and regulatory requirements, So that Ofqual’s data and AI products remain compliant, usable, and effective. As a service designer, I need access to consistent insights and dependable data flows, So that services can be improved and new capabilities introduced based on evidence rather than assumptions. As a citizen accessing Ofqual’s public information, I need accurate, transparent, and accessible data-driven insights, So that I can understand qualifications and regulatory activity without confusion. As a regulated awarding organisation, I need secure, reliable, and well‑managed data services from Ofqual, So that I can submit data, manage compliance activities, and meet regulatory requirements without delays or errors. As an internal data professional (such as a data engineer, data analyst, or data scientist), I need modern, well‑maintained data platforms and clear governance frameworks, So that I can build, analyse, and maintain data products efficiently and to the required standards. Preliminary market engagement: Discussions with suppliers at DigiGov Expo 24th - 25th September, ExCeL, London. Discussions covered Ofqual's context as described on our about us page and our approach to strategic partnership, including our skills needs as set out in this tender. About us page link: https://www.gov.uk/government/organisations/ofqual/about Work done so far: N/A Current phase: Live Existing team: Ofqual’s Digital and Data function is a multi-disciplinary capability that supports the design, development, and operation of digital services and data platforms. The team comprises approximately 30-35 roles across product management, software development, data engineering, quality assurance, user-centred design, and infrastructure. The team operates primarily through two multi-disciplinary squads, each combining product, delivery, design, development, and assurance expertise. These squads work in an agile delivery model, enabling iterative improvements to existing services and the development of new functionality. They collaborate closely with business stakeholders to ensure solutions meet regulatory requirements and user needs. Core functions include: Software Development Data Engineering and Management Product and Design Quality Assurance Infrastructure and Support Incumbent supplier: No Linked projects: OF1050 - Software Development https://redirect.contractawardservice.crowncommercial.gov.uk/project/70559/overview Working arrangements: Work can be done remotely. Security clearance: Baseline Personnel Security Standard (BPSS) Special terms and conditions: • Cyber Essentials Plus • ISO27001 Certified • Supply of resources within 2 weeks (10 working days) from request