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Data engineering: what engineers do, the modern stack, and building UK capability
How UK organisations build the systems that make analytics and AI work — roles, the modern stack, and growing data engineering capability.
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Data engineering is the layer between the systems that produce your data and the people who need to use it. When it is done well, analysts get clean tables to query and AI systems get reliable inputs. When it is neglected, dashboards lag, models drift, and every cross-team data question turns into a ticket.
This topic gathers the guides we publish on what data engineering is, how it differs from related roles, and how UK employers are building in-house capability without trying to recruit scarce senior engineers on the open market.
In this topic
GuideWhat is Data Engineering?What data engineers do, how the role differs from analysts and scientists, the modern data stack, and how UK employers build engineering capability.GlossaryData pipelineWhat a data pipeline is, what it does, batch vs streaming variants, and where pipelines fit in the modern data engineering stack.ComparisonData engineer vs data analystHow the data engineer and data analyst roles differ in scope, tools, day-to-day work, and the path into each — and which one a UK team should hire first.