About the job

Magentic, backed by global technology visionaries like Sequoia Capital, is looking for a brilliant Data Engineer to join their London team, focusing on next-generation agentic AI systems that manage entire workflows in a $3 trillion supply chain and procurement market. The mission is to make global manufacturing supply chains robust while harnessing generative AI ethically and efficiently. As a Data Engineer, you will design, build, and maintain scalable data infrastructure powering Magentic’s intelligent agentic systems, transforming raw supply chain data into structured, actionable insights. Responsibilities include building high-volume ingestion pipelines from global supply chain and procurement systems, defining and managing data schemas and catalogs, ensuring data quality, latency, completeness, and lineage, implementing secure and compliant data practices, collaborating with AI, platform, and product teams to provision data sets and feature tables for analytics and machine learning, and continuously improving efficiency via CI/CD automation, cost/performance tuning, and incident analysis. Ideal candidates have 3+ years of cloud-native data engineering experience in AWS or Azure, advanced Python skills, expertise with batch and streaming frameworks (Spark, Flink, Kafka Streams, Beam), knowledge of schema management and data modeling, experience integrating with APIs, message queues, and third-party SaaS systems, strong familiarity with relational, NoSQL, and data lake systems, expertise in observability and data quality tools, and understanding of data security and governance practices (GDPR, CCPA). Magentic offers a salary of £110K-£120K, competitive equity, hybrid work at London HQ (3-4 days), annual team retreats, and a three-stage interview process including screening, design interview with the CTO, and a half-day in-person session. Note: the role currently only considers candidates already based in the UK for visa purposes.