Lead Analytics Engineer

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  insight and 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.   P