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For Companies At a Glance
- Tasks: Lead the design and evolution of robust data pipelines and platforms for analytics and reporting.
- Company: Join Graphcore, a leader in AI innovation and part of the SoftBank Group.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with diverse teams and excellent career advancement opportunities.
- Why this job: Make a real impact in AI by shaping data solutions that drive decision-making.
- Qualifications: Strong experience in Python, AWS data services, and building production-grade data systems.
The predicted salary is between 80000 - 100000 £ per year.
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, reporting and 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 insight and 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.
Lead Data Engineer in Bristol employer: Cerebras
Contact Detail:
Cerebras Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Engineer in Bristol
✨Tip Number 1
Network like a pro! Reach out to current employees at Graphcore on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing the Lead Data Engineer role. Personal connections can make a huge difference!
✨Tip Number 2
Prepare for technical interviews by brushing up on your Python skills and AWS knowledge. Practice coding challenges and be ready to discuss your past projects in detail. We want to see how you’ve tackled real-world problems!
✨Tip Number 3
Showcase your leadership skills! Be ready to talk about times you've led projects or mentored others. Graphcore values collaboration, so demonstrating your ability to work with both technical and non-technical teams will set you apart.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the Graphcore team. Good luck!
We think you need these skills to ace Lead Data Engineer in Bristol
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead Data Engineer role. Highlight your experience with data pipelines, AWS services, and any relevant projects that showcase your skills in Python and data engineering.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background aligns with Graphcore's mission. Don't forget to mention specific experiences that demonstrate your technical leadership.
Showcase Your Technical Skills: In your application, be sure to highlight your hands-on experience with data orchestration, testing, and deployment practices. Mention any tools or technologies you've used that are relevant to the role, like CI/CD workflows or data modelling.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Cerebras
✨Know Your Data Inside Out
Make sure you’re well-versed in the data engineering stack, especially Python and AWS services like S3 and Lambda. Be ready to discuss your past experiences with building data pipelines and how you’ve tackled challenges in production environments.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've designed reliable data systems that recover from failures. Graphcore values resilience, so be ready to explain your approaches to incident resolution and continuous improvement in your previous roles.
✨Communicate Clearly with Stakeholders
Practice explaining complex technical concepts in simple terms. You’ll need to work with both technical and non-technical stakeholders, so demonstrating your ability to translate business needs into scalable data solutions will set you apart.
✨Demonstrate Leadership and Collaboration
Be prepared to discuss how you’ve provided technical leadership in your previous roles. Share experiences where you’ve mentored others or led design reviews, as this aligns with the collaborative culture at Graphcore.