Data engineer in distributed processing

Описание

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.

Задачи

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.

Требования

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.

Условия

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.