Data engineer in distributed processing

We’re Kingfisher, A team made up of over 74,000 passionate people who bring Kingfisher - and all our other brands: B&Q, Screwfix, Brico Depot, Castorama and Koctas to life. Guided by our purpose Better Homes. Better Lives. For Everyone. We believe a better world starts with better homes, and we work every day to make that a reality. Join us and help shape the future of home improvement.

• Define and drive the data platform and data engineering strategy in line with Group Technology objectives.
• Lead architecture decisions and establish scalable standards and design patterns across data pipelines, storage and processing.
• Partner with Architecture and Product teams to shape long-term platform roadmaps and capabilities.
• Design and deliver production-ready data platforms and pipelines that are scalable, resilient, observable and cost-efficient.
• Champion modern engineering practices including CI/CD, automated testing, DevOps, observability and platform automation.
• Strengthen data quality, governance and security while promoting reusable data products and shared platform capabilities.
• Provide technical leadership across squads and influence senior stakeholders across Engineering, Product, Architecture and Technology.
• Lead business-critical initiatives spanning multiple teams, systems and geographies.
• Coach and mentor engineers, support hiring and onboarding, and help build a strong Data Engineering community.
• Evaluate emerging technologies and introduce tools and approaches that deliver measurable value.
• Drive continuous improvement while balancing quality, speed, cost and risk.

• Deep expertise in distributed data processing, cloud-native systems and modern data architecture.
• Proven experience delivering large-scale data platforms and production-grade pipelines.
• Strong Python and SQL skills, with hands-on experience in Spark, PySpark or Scala.
• Experience with dbt for data modelling and transformation.
• Strong knowledge of cloud platforms such as GCP, Azure or AWS, and services including Databricks, BigQuery or Azure Data Factory.
• Strong understanding of DevOps and DataOps practices and tools, including CI/CD, Git, Terraform, Docker and Kubernetes.
• Experience with data quality tools and testing frameworks such as Great Expectations.
• Deep understanding of batch, streaming and event-driven architecture patterns.
• Experience designing resilient, scalable and observable systems and optimising platforms for performance and cost.
• A track record of setting engineering standards, raising capability and driving continuous improvement across teams.
• The ability to act as a trusted technical authority and influence strategic direction, investment decisions and executive-level stakeholders.
• Strong problem-solving and decision-making skills, with confidence working through ambiguity, transformation and changing priorities.
• Experience coaching engineers and contributing to high-performing teams and engineering communities.

• We believe in flexibility and balance. Our hybrid model blends home working for focus with time spent connecting and collaborating - whether in our offices or at offsite locations.
• On average within our Engineering team - 20% of your time involving in-person collaboration.
• An inclusive environment where your potential is limited only by your imagination. We encourage new ideas, support experimentation, and strive to create a workplace where everyone can be their best self.
• We also offer a competitive benefits package and plenty of opportunities to stretch and grow your career.