Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Engineer

Morgan Spencer
City of London
3 days ago
Create job alert

Salary: Competitive, negotiable with possible equity in the medium term


Overview

This rail software and consulting company works with leading organisations across the UK rail industry, helping them harness data to solve complex operational challenges. Data Engineers are key to this mission - building robust data infrastructure and tooling that powers insights, analytics, and software products used across the rail network.


The Role

As a Data Engineer, you'll be part of a collaborative technical team, working across the data lifecycle: from designing ETL pipelines and integrating real-time data streams, to developing APIs and backend systems that deliver rail data securely and reliably. You'll work closely with engineers, consultants, and project managers to translate real-world rail problems into scalable technical solutions. This role sits at the intersection of software engineering, data architecture, and delivery.


Responsibilities


  • Data Engineering & Infrastructure

    • Design and implement robust data pipelines (batch and real-time) for ingesting, transforming, and serving rail-related datasets.
    • Develop and maintain data APIs and services to support analytics, software features, and reporting tools.
    • Build data models and storage solutions that balance performance, cost, and scalability.
    • Contribute to codebases using modern data stack technologies and cloud platforms (e.g., Azure, AWS).



  • Collaborative Delivery

    • Work with domain consultants and delivery leads to understand client needs and define data solutions.
    • Participate in agile delivery practices, including sprint planning, reviews, and retrospectives.
    • Help shape end-to-end solutions — from ingestion and transformation to client-facing features and reporting.



  • Best Practices & Growth

    • Write clean, well-documented, and tested code following engineering standards.
    • Participate in design reviews, code reviews, and collaborative development sessions.
    • Stay up-to-date with new tools and trends in the data engineering space.
    • Contribute to internal learning sessions, tech talks, and shared documentation.



Qualifications

  • You might be a good fit if you have experience with:
  • Building ETL/ELT pipelines using tools like Kafka, dbt, or custom frameworks.
  • Working with structured and unstructured data at scale.
  • Backend development in Python (or similar), and familiarity with data APIs.
  • Cloud data platforms (e.g., AWS Redshift, Azure Synapse).
  • SQL and database design for analytics, reporting, and product use.
  • Agile collaboration with cross-functional teams.
  • You don’t need experience in rail — just curiosity and a willingness to learn the domain.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Engineering Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data engineering hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise reliable pipelines, modern lakehouse/streaming stacks, data contracts & governance, observability, performance/cost discipline & measurable business outcomes. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for platform‑oriented DEs, analytics engineers, streaming specialists, data reliability engineers, DEs supporting AI/ML platforms & data product managers. Who this is for: Data engineers, analytics engineers, streaming engineers, data reliability/SRE, data platform engineers, data product owners, ML/feature‑store engineers & SQL/ELT specialists targeting roles in the UK.

Why Data Engineering Careers in the UK Are Becoming More Multidisciplinary

For many years, data engineering in the UK meant designing pipelines, moving data between systems, and ensuring analysts had what they needed. Today, the field is expanding. With cloud platforms, machine learning, real-time analytics and the explosion of sensitive personal data, employers expect data engineers to do much more. Modern data engineering is no longer just about code and storage. It requires legal awareness, ethical judgement, psychological insight, linguistic clarity and human-centred design. These disciplines shape how data is collected, processed, explained and trusted. In this article, we’ll explore why data engineering careers in the UK are becoming more multidisciplinary, how law, ethics, psychology, linguistics & design now influence job descriptions, and what job-seekers & employers must do to thrive.

Data Engineering Team Structures Explained: Who Does What in a Modern Data Engineering Department

Data has become the lifeblood of modern organisations. Every sector in the UK—finance, healthcare, retail, government, technology—is increasingly relying on insights derived from data to drive decisions, deliver products, and improve operations. But raw data on its own isn’t enough. To make data useful, reliable, secure, and scalable, companies must build strong data engineering teams. If you’re recruiting for data engineering or seeking a role, understanding the structure of such a team and who does what is essential. This article breaks down the typical roles in a modern data engineering department, how they collaborate, required skills and qualifications, expected UK salaries, common challenges, and advice on structuring and growing a data engineering team.