Principal Data Engineer Data Technology

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We are currently seeking an experienced professional to join our team in the role of Principal Data Engineer Data Technology.Business: CTO Data Technology Job ID：57085 The Role

As Principal Engineer for the Data Technology Platform you will set technical strategy, architecture and engineering standards across core enterprise data capabilities. The platform estate spans Enterprise Data Assets (EDA), Reference Data, Big Data and Movement and Data Decisioning engineering that underpin data democratisation, AI enablement, customer insight and regulatory compliance. You will shape how distributed data platforms are designed, built and run in hybrid cloud environments so they remain enterprise-ready and future-fit. This role combines deep hands-on engineering direction with influence across product and delivery teams in a global matrixed organisation. Success means clear reference engineering standards, consistent platform patterns and measurable improvements in scalability, observability and cost. You will also strengthen the developer experience so teams can discover, adopt and build on shared data services at pace.

Principal responsibilities

• Define and evolve reference engineering standards for core data provisioning platforms aligned to Group Data Strategy and Data Future State Architecture

• Set technical direction across Enterprise Data Assets (EDA) including APIs for standardised data provisioning

• Establish engineering approaches for Reference Data Services including golden source alignment and hierarchy management

• Oversee architecture and engineering patterns for big data ingestion, streaming and transformation at scale

• Shape decisioning infrastructure including real-time feature stores and orchestration

• Govern peer reviews to improve consistency, reusability and compliance with enterprise standards

• Champion DevSecOps, CI/CD and infrastructure-as-code across engineering teams

• Advance observability, performance engineering, cost optimisation and scalability in hybrid cloud environments

• Guide teams on data pipelines, APIs, metadata-driven controls and automated testing frameworks

• Represent the domain in cross-platform technology councils and architecture forums

Knowledge & Experience/Qualifications

• Bring substantial hands-on experience in data platform engineering, architecture or software development in a scaled enterprise environment

• Build large-scale data pipelines, APIs and event-driven systems using modern frameworks and technologies such as Spring, Kafka and Spark