DevOps Data Platform Engineer
hace 2 días
London
Senior Platform Engineer £Join one of the UK's leading online retailers as they evolve their next-generation data platform. This is an opportunity to shape the backbone of a modern data ecosystem, empowering analysts, ML engineers, and data scientists to deliver smarter, faster insights at scale. You'll play a key role in designing and engineering platform services that treat data as a core product. This means building scalable, secure, and observable systems that help teams confidently leverage data across the business. You'll work closely with a wide range of technical and non-technical partners to deliver resilient infrastructure, champion data governance, and mentor others in engineering excellence. Shape the data platform roadmap: Introduce modern observability, quality, and governance frameworks that elevate how teams access and trust data. Develop services, APIs, and data pipelines using modern cloud tooling and automation-first principles. Implement CI/CD pipelines, testing frameworks, and container-based deployments to ensure reliability and repeatability. Collaborate with product engineers, data scientists, and ML practitioners to understand their workflows and deliver high-impact platform solutions. Proactively monitor system performance, automate incident response, and strengthen platform resilience. Strong proficiency in Python (or a similar high-level language) with a deep understanding of software engineering best practices - testing, automation, clean code, and CI/CD. Proven track record building and maintaining scalable data platforms in production, enabling advanced users such as ML and analytics engineers. Hands-on experience with modern data stack tools - Airflow, DBT, Databricks, and data catalogue/observability solutions like Monte Carlo, Atlan, or DataHub. Solid understanding of cloud environments (AWS or GCP), including IAM, S3, ECS, RDS, or equivalent services. Experience rolling out data governance and observability frameworks, including lineage tracking, SLAs, and data quality monitoring. Familiarity with modern data lake table formats such as Delta Lake, Iceberg, or Hudi.