Analytics Engineer

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.

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.

Key Responsibilities:

• Cross-industry data product delivery
• Engage with functional teams across DFTO, TOCs, NR, and RDG to translate domain expertise and analytical need into well-scoped, deliverable data product designs.
• 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 and which support consistent, reusable analytics across the industry.
• Develop the analytical and presentation layer on top of shared data products 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.
• 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.

Data integration and modelling:

• Build and maintain data ingestion pipelines across a multi-cloud platform environment.
• Design and implement layered data transformations from raw ingestion through to cleansed, analytics-ready models.
• Develop reusable, generalisable ingestion and transformation patterns.
• Contribute to shared data standards across the ecosystem.
• Support cross-organisational data sharing at a technical level.

Data engineering standards and governance practices:

• Apply DataOps disciplines consistently across all delivery.
• Contribute to the definition and continuous improvement of shared data engineering standards.
• Maintain data quality and data catalogue entries across assigned products.
• Identify and surface delivery-level friction as structured inputs to the data standards and governance function.

Stakeholder and community engagement:

• Operate across organisational boundaries as a matter of routine.
• Support the wider community of data analysts and engineers across the federated TOC, NR, RDG ecosystem.

Knowledge, Skills, Experience & Technical Qualifications:

• Strong SQL and proficiency in at least one analytics programming language, with Python strongly preferred.
• Hands-on experience building and maintaining data ingestion and transformation pipelines.
• Familiarity with layered data modelling approaches and transformation frameworks.
• Comfort working within cloud-native data platform environments.
• DataOps practices: CI/CD pipelines, Git versioning, and environment lifecycle management.
• Familiarity with data visualisation and BI tooling.
• Strong analytical problem-solving ability.
• Ability to work independently across organisational boundaries.
• Clear written and verbal communication.

Desirable:

• Experience and delivery capability is more important than formal qualifications.
• A degree in a STEM, quantitative, or related field may be beneficial but is not required.
• Familiarity with data catalogue and data governance tooling.
• Exposure to semantic modelling, ontology design, or reference data management.
• Experience working in multi-stakeholder environments.
• Familiarity with railway industry data sources is desirable but not expected.

The postholder will be part of a new central Data function within DFTO DDaT, working alongside a Principal Analytics Engineer and under the strategic direction of the Group Head of Data. The wider working community spans data professionals across publicly owned TOCs, NR, and RDG, all working toward the shared data capability which Great British Railways will require.

Vacancy Details:

• Duration: Permanent
• Location: London Waterloo
• Salary: up to £72,700
• Closing date: 16th June 2026

DFTO Benefits:

• Annual Leave: Starting at 25 days and rising to an additional day per year of service completed within the first 5 completed years up to a maximum of 5 additional (30 days)
• DC Pension Scheme: 10% Employer contribution, 5% Employee contribution
• Opportunities to learn and network across the wider industry

About our people and the recruitment process - We're an inclusive employer of choice and we welcome applications from everyone! We encourage our colleagues to work flexibly, as we know traditional working patterns don't always fit.

If you want to consider working flexibly, just let us know and we'll do our best to help and invest in your career with us, whilst you have a healthy work life balance.

Contact: If you have any questions or reasonable adjustments, please contact Amra.Hurley@dftoperator.co.uk. Please do not email any CV's to us, your application must be made by clicking the 'Apply' button.