About us 

Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. 

As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. 

Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore brings together deep expertise to solve complex problems and deliver meaningful progress in AI compute. 

Job Summary 

Reporting to the Head of Data & Analytics, the Lead Analytics Engineer is a senior individual contributor responsible for owning the analytics engineering layer within Graphcore’s data platform. This role focuses on building and evolving curated data models, trusted metrics and well-documented semantic structures that enable reliable self-service analytics across the business. A key part of the role is partnering closely with stakeholders across business and technical functions to understand how teams operate, build trusted relationships, and translate real decision-making needs into clear, usable and governed datasets that support reporting, planning and operational insight. 

The Team 

The Data & Analytics team enables better decision-making across Graphcore by building trusted data foundations, scalable platforms and high-quality data products. The team works across a broad range of business and technical domains, partnering with colleagues throughout the company to improve access to reliable information, strengthen operational insightand support efficient, data-informed ways of working. Within this team, the Lead Analytics Engineer owns a key part of the analytics workflow, acting as a bridge between business stakeholders and data engineers to shape data models that reflect how the business works and can be adopted with confidence. 

Responsibilities and Duties 

• Own the dbt transformation layer, building, maintaining and evolving data models that support reliable self-service analytics across Graphcore. 

• Build strong working relationships with stakeholders across business and technical functions to understand priorities, processes, definitions and decision-making needs. 

• Work closely with stakeholders to discover, clarify and challenge requirements, turning ambiguous questions into well-structured analytical datasets and trusted metrics. 

• Translate business processes and raw datasets into intuitive, flexible and governed analytical models that support reporting, planning and operational decision-making. 

• Design clear, maintainable SQL models with a well-structured approach to naming, layering, reuse and long-term sustainability. 

• Partner with stakeholders to define, document and maintain trusted metric and KPI logic, ensuring consistency as requirements evolve. 

• Implement robust testing, validation and documentation practices in dbt to improve data quality, trust and discoverability. 

• Work closely with Data Engineering to align on source data structures, manage upstream schema changes and support reliable downstream consumption. 

• Establish and maintain CI/CD practices for analytics engineering, including automated checks, review workflows and safe release processes. 

• Optimise model performance and warehouse efficiency through pragmatic design choices, including incremental approaches, efficient joins and platform-aware tuning. 

• Support self-service analytics by creating datasets that are easy to understand and consume, with clear documentation and guidance for common use cases. 

• Contribute to the effective use of visualisation and reporting tools by modelling data for dashboard performance, usability and consistency. 

• Apply appropriate governance and access control principles to analytical datasets, working with colleagues to support secure and appropriate self-service access. 

• Help shape analytics engineering standards and day-to-day practices within the wider Data & Analytics function through collaboration, review and continuous improvement. 

Candidate Profile 

Essential 

• Demonstrable experience building production-quality dbt models that enable reliable self-service analytics. 

• Strong SQL skills and experience designing maintainable transformation layers within a modern data platform. 

• Proven ability to build strong relationships with stakeholders and work closely with business users to understand requirements, processes and data needs. 

• Proven ability to translate business requirements and raw datasets into flexible, intuitive data models that stakeholders can use confidently. 

• Strong grasp of analytics engineering best practices, including model layering, documentation, testing and semantic consistency. 

• Experience defining and maintaining trusted metrics, KPIs and curated datasets for business use. 

• Strong understanding of data quality, change management and the practices needed to maintain trust in analytical outputs. 

• Experience applying CI/CD practices to analytics workflows, including automated testing, deployment discipline and review processes. 

• Experience working with relational databases and analytical warehouse technologies. 

• Strong communication skills, including the ability to influence decisions, challenge assumptions constructively and work effectively with both technical and non-technical stakeholders. 

• A practical, delivery-focused approach to problem solving. 

Desirable 

• Experience with data warehouse technologies such as Redshift, PostgreSQL or ClickHouse. 

• Experience supporting self-service visualisation and reporting tools such as Superset, Metabase or similar platforms. 

• Familiarity with semantic or metrics-layer tooling. 

• Python experience, including building lightweight data applications or utilities. 

• Experience improving dataset discoverability, documentation and adoption across an organisation. 

• Familiarity with data governance practices, including access control and sensitive data handling. 

• Experience working in a Git and pull-request based development workflow. 

• Experience working in a fast-moving product, technology or engineering-led environment. 

About us 

Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. 

As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. 

Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. We bring together specialists across AI research, silicon design, software engineering and systems to solve complex problems and deliver meaningful impact. 

Job Summary 

Reporting into the Data & Transformation function, the Project Manager is responsible for delivering cross-functional transformation programmes that improve how Graphcoreoperates day to day. The role owns end-to-end delivery of initiatives that shape business processes, ways of working and change around enterprise platforms and operational activities, partnering closely with teams across IT, Finance, People, Operations and external partners to ensure outcomes are delivered in a structured, effective and sustainable way. 

The Team 

The Data & Transformation team delivers programmes that improve business processes, tooling and ways of working across Graphcore. The team focuses on shaping and landing transformation around systems and operational processes, rather than owning the systems themselves. It works across multiple functions to deliver change successfully, balancing operational needs, governance, user adoption and long-term sustainability. The team partners closely with subject matter experts, Business Analysts, technical teams and external vendors to turn business requirements into well-executed delivery. 

Responsibilities and Duties 

• Own end-to-end delivery of cross-functional projects, including scope, plans, milestones, dependencies, risks, assumptions, issues and decisions. 

• Establish and run effective project governance, including delivery cadences, status reporting, change control, clear ownership and decision tracking. 

• Coordinate delivery from initiation through go-live and stabilisation, covering planning, execution, testing, user acceptance, cutover and hypercare. 

• Partner with Business Analysts and subject matter experts to translate agreed requirements and process designs into executable delivery plans. 

• Drive alignment across internal teams and third-party partners, resolving blockers, managing dependencies and maintaining momentum against agreed outcomes. 

• Define delivery milestones, acceptance criteria and readiness checkpoints to support high-quality implementation and controlled release. 

• Ensure change is landed effectively through communication planning, training coordination, operational readiness and adoption tracking. 

• Support post-go-live follow-through, including defect triage, prioritisation, lessons learned and continuous improvement activity. 

• Ensure changes are landed in a supportable way, with clear ownership, operating processes, documentation and service expectations agreed with the relevant teams where appropriate. 

• Work with stakeholders to ensure delivery plans appropriately consider access controls, security, auditability and policy or compliance requirements. 

• Manage vendor and partner deliverables where required, ensuring expectations, responsibilities, timelines and dependencies are clearly understood. 

• Produce clear project artefacts and updates that enable informed decision-making and transparent communication across stakeholders. 

Candidate Profile 

Essential 

• Proven experience delivering cross-functional business systems and operational change initiatives, including implementations, migrations, integrations or significant process change. 

• Strong project management fundamentals, including planning, dependency management, risk and issue management, governance and stakeholder communication. 

• Experience coordinating delivery across technical and non-technical teams through testing, go-live and stabilisation. 

• Ability to work effectively in a delivery model that includes Business Analysts or equivalent partners responsible for detailed requirements and process analysis. 

• Strong written communication skills, with the ability to produce clear and effective plans, status updates, RAID logs and decision records. 

• Experience using modern delivery tools such as Jira and Confluence, or comparable platforms. 

• Strong organisational skills, with the ability to manage competing priorities and keep delivery on track in a fast-moving environment. 

• Strong collaboration and relationship-building skills, with the confidence to work across multiple functions and with external partners. 

Desirable 

• Experience delivering change across enterprise domains such as Finance, People systems, IT service management, procurement, workplace systems or identity and access management. 

• Experience planning and coordinating data migration, cutover activity and operational transition for enterprise systems. 

• Familiarity with security and access control concepts, including role-based access, least privilege and joiner, mover, leaver processes. 

• Experience working in environments with policy, audit or regulatory considerations. 

• Experience working on multi-vendor delivery programmes, organisational integration initiatives or large-scale business change. 

• Interest in, or experience with, AI-enabled workflow improvements and business system integrations. 

About us 

Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. We develop hardware, software and systems infrastructure that unlock the next generation of AI breakthroughs and enable the widespread adoption of AI solutions across every industry. 

As part of the SoftBank Group, we are part of a network of companies building some of the world’s most transformative technologies. Together, we share an ambitious vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. 

Our teams bring together diverse perspectives across AI research, silicon design, software engineering and systems architecture. We combine deep expertise with a practical, collaborative approach to solving complex problems and turning ideas into real-world impact. 

Job Summary 

Reporting to the Head of Data & Transformation, the Business Transformation Lead is a senior individual contributor responsible for shaping and delivering complex, cross-functional change across systems, data and business processes. This role leads high-impact transformation work from discovery through implementation, combining strategic thinking with hands-on execution to improve how Graphcore operates and scales. 

Operating across business and technology domains, you will translate ambiguity into clear direction, define target outcomes, assess solution options and work closely with delivery teams to implement change. You will also provide guidance and structure to business analysts contributing to initiatives, and partner closely with a project manager to help coordinate and deliver projects effectively. You will act as a trusted partner to stakeholders, bringing structure, technical insight and practical problem-solving to initiatives that span multiple functions. 

The Team 

The Data & Transformation team sits within Graphcore’s broader business operations and technology environment. We are responsible for driving enterprise-wide change across systems, data and processes, helping the business work more effectively, make better decisions and scale in a sustainable way. 

We partner closely with teams across Finance, People, IT and other operational functions to identify opportunities, design improved ways of working and deliver technology-enabled transformation. Our work spans business analysis, process design, data improvement, solution shaping and change delivery. 

Responsibilities and Duties 

• Lead complex transformation initiatives across multiple business domains, from discovery and problem definition through to implementation and embedding. 

• Define clear problem statements, scope, success measures and delivery approaches aligned to business priorities and operational goals. 

• Partner with senior stakeholders to align on outcomes, priorities, trade-offs and decision-making, building momentum across cross-functional programmes. 

• Analyse current processes, systems and data flows to identify root causes, inefficiencies, risks and opportunities for improvement. 

• Design scalable end-to-end business processes, operating models, governance approaches and controls that support effective execution. 

• Evaluate solution options, including process, system and data changes, balancing business value, technical feasibility, integration complexity and long-term maintainability. 

• Work hands-on with data, workflows and system requirements, using tools such as SQL, Python or low-code platforms to explore issues, validate assumptions, prototype ideasand support solution design. 

• Translate business needs into clear requirements, user stories, process maps, data definitions and acceptance criteria that enable efficient delivery. 

• Collaborate closely with technical teams to shape solutions, resolve design questions and ensure alignment across applications, integrations and data structures. 

• Support delivery through build, test and release activities, helping teams prioritise backlogs, clarify requirements and maintain focus on measurable outcomes. 

• Provide day-to-day guidance and support to business analysts working across transformation initiatives, helping to raise quality, consistency and delivery effectiveness. 

• Partner closely with a project manager to support planning, coordination, dependency management and execution across complex projects. 

• Define and track KPIs and other success measures to assess impact, inform decision-making and drive continuous improvement. 

• Lead change readiness activities, including adoption planning, documentation, knowledge transfer and transition into business-as-usual operations. 

• Establish and promote strong transformation and analysis practices, raising the quality of delivery across initiatives and supporting colleagues through coaching and practical guidance. 

Candidate Profile 

Essential 

• Experience leading complex, cross-functional business transformation initiatives involving systems, data and process change. 

• Proven ability to operate at both strategic and delivery levels, shaping direction while remaining close to the detail. 

• Strong stakeholder management and influencing skills, with the ability to build alignment across senior business and technical audiences. 

• Experience supporting or guiding other analysts and working closely with project or programme management to deliver complex change. 

• Experience defining target operating models, business processes, governance approaches and success measures. 

• Strong business analysis capability, including requirements management, process mapping, problem structuring and solution assessment. 

• Practical technical fluency in areas such as data analysis, systems thinking, integrations or automation. 

• Hands-on experience using tools such as SQL, Python or equivalent approaches to analyse data, test ideas or support solution development. 

• Ability to work effectively in ambiguity, turning complex problems into clear, actionable plans. 

• Experience partnering with delivery teams across build, testing, rollout and adoption phases. 

• Strong written and verbal communication skills, with the ability to adapt messages for different audiences. 

Desirable 

• Experience in a high-growth or technology-led environment. 

• Experience working across enterprise domains such as Finance, People, IT or business operations. 

• Familiarity with SaaS implementation, vendor selection or process automation initiatives. 

• Experience with data governance, data quality improvement or migration activities. 

• Familiarity with cloud-based platforms and modern enterprise application ecosystems. 

• Experience using AI-assisted tools or approaches to improve analysis, delivery or operational effectiveness. 

About us 

Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. 

As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. 

Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore brings together deep expertise to solve complex problems and deliver meaningful progress in AI compute. 

Job Summary 

Reporting to the Head of Data & Analytics, the Lead Data Engineer is a senior individual contributor responsible for leading a key area of Graphcore’s data platform and engineering practices. This role combines hands-on technical delivery with technical leadership across data pipelines, platform capabilities and data products that support analytics, reportingand operational decision-making. Working closely with stakeholders across technical and business functions, the Lead Data Engineer helps shape the direction of the data platform, drives improvements to reliability, scalability and governance, and enables teams across Graphcore to make better use of trusted data. 

The Team 

The Data & Analytics team enables better decision-making across Graphcore by building trusted data foundations, scalable platforms and high-quality data products. The team works across a broad range of business and technical domains, partnering with colleagues throughout the company to improve access to reliable information, strengthen operational insightand support efficient, data-informed ways of working. Within this team, the Lead Data Engineer plays a key role in evolving the platform, setting engineering standards and delivering robust solutions that scale with business needs. 

Responsibilities and Duties 

• Lead the design, build and evolution of robust data pipelines and platform services that support analytics, reporting and operational use cases across Graphcore. 

• Own the data engineering stack, planning and delivering improvements to reliability, scalability, maintainability, performance and security. 

• Build and operate Python-based batch and streaming workflows, with clear approaches to orchestration, testing, deployment, monitoring and incident resolution. 

• Design and implement data solutions on AWS using services such as S3, Lambda, Aurora PostgreSQL, Athena, Glue and Redshift, ensuring they are secure, resilient and cost-conscious. 

• Define and apply engineering standards for data quality, observability, documentation, release processes and operational support. 

• Partner with analysts, engineers and business stakeholders to translate requirements into trusted datasets, well-structured data models and reusable data products. 

• Drive improvements to platform resilience through approaches such as idempotent processing, retry and recovery mechanisms, buffering strategies and backfill or replay capabilities. 

• Lead technical decision-making in your area by reviewing designs and code, sharing expertise and helping to raise the quality bar for data engineering across the team. 

• Build and maintain CI/CD workflows and development practices that enable safe, repeatable and efficient delivery of data infrastructure and workflows. 

• Ensure appropriate data protection and access controls are in place, including least-privilege access, secure secrets handling and suitable database permissions. 

• Contribute to the development of internal tools and lightweight applications that improve access to data and support self-serve workflows. 

• Work across teams to identify opportunities for platform and process improvements, helping shape the direction of data engineering within the wider Data & Analytics function. 

Candidate Profile 

Essential 

• Strong experience designing, building and operating production-grade data pipelines and data platforms in Python. 

• Strong hands-on experience with modern data orchestration, testing, deployment and monitoring practices in a production environment. 

• Experience building solutions on AWS data services, including storage, processing and query technologies. 

• Strong understanding of data modelling, data quality, schema design and performance optimisation across relational and analytical systems. 

• Experience designing reliable data systems that recover gracefully from failure and operate effectively in real-world production conditions. 

• Experience working with batch and streaming data pipelines, including operational support, troubleshooting and continuous improvement. 

• Strong knowledge of security and access control principles for data platforms, including IAM, database permissions and secure handling of credentials and secrets. 

• Experience providing technical leadership as a senior individual contributor through design reviews, code reviews, standards-setting and mentoring of others. 

• Ability to work effectively with both technical and non-technical stakeholders, turning business needs into practical, scalable data solutions. 

• Strong communication skills, with the ability to explain technical decisions clearly and influence outcomes across teams. 

Desirable 

• Experience with Prefect or a similar workflow orchestration platform. 

• Experience with streaming or data collection technologies. 

• Experience with PostgreSQL, Redshift, ClickHouse or similar database and warehouse technologies. 

• Experience with CI/CD tooling and Infrastructure as Code approaches. 

• Experience building lightweight internal tools or data applications using Python frameworks such as Streamlit or Flask. 

• Familiarity with dbt and working models that combine data engineering and analytics engineering. 

• Understanding of operational best practices for cloud-based data platforms, including cost optimisation and observability. 

• Experience working in a fast-moving product, technology or engineering-led environment.