Analytics Engineer

About DFT Operator

Join Our Team at DFTO

DFTO is the government’s public sector rail owning group. Its purpose is to bring all currently privately‑owned train operators into public ownership in advance of the creation of Great British Railways in 2027 – and deliver improvements in the here and now by unifying and integrating train operations under common public ownership.

DFTO has over 30,000 employees, runs over 8,500 services a day and delivers over 640 million customer journeys across its networks every year. 7,000 people joined the railway family in the last year

Major improvements are being delivered by DFTO train operators (TOCs) that are already under public ownership – these are LNER, Northern, Trans Pennine Express (TPE), Southeast, South Western Railway (SWR), c2c, Greater Anglia and WM Trains.

We work closely with the DfT but operate independently with our own governance and leadership teams. Our priority is ensuring efficient, dependable rail services for everyone.

The Analytics Engineer is a core member of the DFTO Data function, responsible for the hands‑on design and delivery of data products across the Common Data Service portfolio. The portfolio is DFTO’s cross‑industry data capability: ingesting, standardising, and publishing shared data products for use across the GB rail ecosystem, in preparation for the establishment of Great British Railways.

This is a full‑stack data delivery role, combining data engineering, analytical modelling, and cross‑organisational working. The postholder takes end‑to‑end ownership of their data products – from problem definition and ingestion pipeline design through to the analytical and presentation layer that makes those products discoverable, interpretable, and usable by functional teams across the GB railway ecosystem. The environment is genuinely multi‑organisational from day one: the postholder will work with counterparts across train operating companies (TOCs), Rail Delivery Group (RDG), and Network Rail () as delivery peers, earning credibility through the quality and consistency of their engineering output.

• Engage with functional teams across DFTO, TOCs, , and RDG to translate domain expertise and analytical need into well‑scoped, deliverable data product designs, working with the Principal Analytics Engineer to maintain engineering coherence across concurrent initiatives.
• Build and deliver shared data products that are catalogued, governed, discoverable, and engineered to a standard that remains maintainable beyond the initial build effort.
• Design data models that reflect real‑world railway concepts (e.g., passenger experience, train service delivery, rolling stock) and which support consistent, reusable analytics across the industry.
• Develop the analytical and presentation layer on top of shared data products (e.g., summaries, visualisations, and @contextual documentation) so that the output is usable by functional teams on a self‑serve basis.
• Ensure data products are structured, documented, and published in a way that supports machine learning, AI, and workflow automation use cases – including clearschema definitions, quality metadata, and access patterns that can be consumed programmatically.
• Document data processes, schemas, and transformation logic to a standard that allows engineers and analysts outside the central team to understand, validate, and build upon the outputs.

• Build and maintain data ingestion pipelines across a multi‑cloud platform environment, drawing in feeds from operational, performance, commercial, and third‑party source systems across the railway ecosystem.
• Design and implement layered data transformations from raw ingestion through to cleansed, analytics‑ready models, maintaining adherence to agreed architectural patterns.
• Develop reusable, generalisable ingestion and transformation patterns rather than bespoke per‑source implementations, so that adding a new data source to the portfolio is a configuration exercise rather than a new engineering project.
• Contribute to shared data standards across the ecosystem –…