The posting, in Ocado's own words
archived Oct 19, 2026Data Engineer (Modelling & Transformation)| Hybrid Working | Hatfield
Introduction:
We are Ocado Group, and we're bringing world-class automation to online grocery. Our Ocado Smart Platform (OSP) combines cutting-edge robotics, AI, and IoT within our advanced CFCs (Customer Fulfilment Centres). We've mastered the single pick, transforming online delivery for our global partners. Join us and be part of a team pushing the boundaries of retail technology.
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About the Role:
As a Data Engineer within our Data Engineering Modelling and Transformation team, you will be directly responsible for building and maintaining the foundational data warehouse that powers analytics, reporting, machine learning, and partner data products across Ocado Technology . In this role, you will transform raw operational data into trusted, governed, and business-ready datasets that drive strategic and operational decision-making across the entire organisation . Working in an agile environment, you will collaborate closely with data scientists, analysts, product owners, and platform engineers to deliver high-quality data feeds and scalable transformation frameworks . You will focus on designing reliable ELT/ETL pipelines, establishing rigorous data quality controls, and optimizing performance across our cloud data warehouse infrastructure to ensure seamless downstream data delivery for all enterprise consumers .
Key Responsibilities:
Responsible for building and maintaining the core data warehouse that powers analytics, reporting, machine learning, and partner data products . Design, develop, and maintain scalable, reliable ELT/ETL pipelines across enterprise data solutions . Build and optimise dimensional and analytical data models to meet complex business reporting and analytics needs . Develop and maintain reusable data transformation logic using modern software engineering best practices . Implement automated data quality checks, pipeline monitoring, and testing frameworks to ensure data reliability . Collaborate with analysts, data scientists, product teams, and platform engineers to deliver secure, business-ready datasets . Monitor, troubleshoot, and optimise pipeline performance to continuously improve efficiency and operational resilience . Participate in code reviews and actively contribute to continuous improvements in team engineering standards . Produce clear documentation and foster knowledge sharing across the craft .