Staff Software Engineer

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 enjoys a culture of continuous learning and constant innovation.

Reporting to the Head of Data & Transformation, the Staff Data Engineer is a senior individual contributor responsible for designing, building, and improving key parts of Graphcore's data platform. This role blends hands-on engineering with technical leadership. You will work closely with engineers, analysts, and business partners to deliver reliable, scalable data solutions for analytics, reporting, and operational decisions. You will help set engineering guidelines, contribute to the platform's growth, and assist other engineers through technical advice and mentoring.

The Data & Analytics team drives improved decision-making throughout Graphcore by building dependable data foundations, scalable platforms, and superior data products. The team collaborates widely across business and technical areas, working with colleagues to increase access to accurate information. They strengthen operational understanding and foster effective, data-driven practices. As a senior member, the Staff Data Engineer supports ongoing platform development, encourages engineering protocols, and contributes to delivering robust technical solutions across the data estate.

• Architect, assemble, and upgrade durable data pipelines and platform services that support analytics, reporting, and operational workloads.
• Lead key elements of the data engineering platform, contributing to better reliability, scalability, maintainability, and operational performance.
• Develop and manage Python-based batch and streaming data workflows, including orchestration, testing, deployment, and monitoring.
• Build and maintain secure, resilient, and cost-effective data solutions using AWS services like S3, Lambda, Aurora PostgreSQL, Athena, Glue, and Redshift.
• Contribute to engineering standards covering data quality, documentation, testing, observability, and operational support, helping ensure consistent delivery across the team.
• Partner with analysts, software engineers, and business collaborators to develop trusted datasets, reusable data models, and scalable data products.
• Improve platform resilience through robust error handling, recovery mechanisms, replay processes, and operational automation.
• Provide technical leadership through design reviews, code reviews, mentoring, and sharing engineering guidelines.
• Build and maintain CI/CD pipelines and engineering workflows that enable safe, repeatable, and efficient delivery.
• Ensure appropriate security controls, data governance, and access management are implemented across the platform.
• Build internal tools and lightweight applications designed to increase data availability and facilitate self-service options.
• Find ways to improve engineering practices, platform capabilities, and delivery processes, working collaboratively with colleagues across the Data & Analytics team.

• Solid expertise in architecting, implementing, and maintaining production-quality data pipelines and platforms using Python.
• Robust practical experience in contemporary data orchestration, testing, deployment, and monitoring methods within production settings.
• Experience developing cloud-based data solutions using AWS services.
• Solid grasp of data modeling, schema design, data quality, and performance tuning across relational and analytical systems.
• Experience designing resilient data systems that recover gracefully from operational failures.
• Experience handling both batch and streaming data pipelines in production.
• Solid knowledge of security, access control, and governance for cloud-based data platforms, including IAM, database permissions, and secure secrets management.
• Experience offering technical guidance via design reviews, code reviews, and mentoring fellow engineers.
• Ability to work effectively with technical and non-technical collaborators to translate business requirements into scalable data solutions.
• Strong communication skills with the ability to explain technical concepts clearly and build effective working relationships across teams.

• 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 data warehouse technologies.
• Experience with CI/CD tooling and Infrastructure as Code.
• Experience building lightweight internal tools using Python frameworks such as Streamlit or Flask.
• Familiarity with dbt and analytics engineering practices.
• Experience improving observability, operational monitoring, and cloud cost optimization.
• Experience contributing to technical roadmaps and platform improvements within a collaborative engineering team.

We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.