Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and implement data pipelines, develop APIs, and solve real-world rail challenges.
- Company: Dynamic rail software company with a focus on innovation and collaboration.
- Benefits: Competitive salary, negotiable equity, and opportunities for professional growth.
- Why this job: Join a team that transforms data into impactful solutions for the rail industry.
- Qualifications: Experience in ETL pipelines, backend development, and cloud platforms is a plus.
- Other info: Curiosity and a willingness to learn are key; no rail experience needed!
The predicted salary is between 36000 - 60000 ÂŁ per year.
Salary: Competitive, negotiable with possible equity in the medium term.
Company: This business is a rail software and consulting company with a growing team and a solid foundation of project‑based revenue. It works with leading organisations across the UK rail industry, helping them harness data to solve complex operational challenges.
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.
Key Responsibilities
- Data Engineering & Infrastructure: Design and implement robust data pipelines (batch and real‑time) for ingesting, transforming, and serving rail‑related datasets.
- Data Engineering & Infrastructure: Develop and maintain data APIs and services to support analytics, software features, and reporting tools.
- Data Engineering & Infrastructure: Build data models and storage solutions that balance performance, cost, and scalability.
- Data Engineering & Infrastructure: 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.
- Collaborative Delivery: Participate in agile delivery practices, including sprint planning, reviews, and retrospectives.
- Collaborative Delivery: 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.
- Best Practices & Growth: Participate in design reviews, code reviews, and collaborative development sessions.
- Best Practices & Growth: Stay up‑to‑date with new tools and trends in the data engineering space.
- Best Practices & Growth: Contribute to internal learning sessions, tech talks, and shared documentation.
The Candidate
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.
Data Engineer employer: Morgan Spencer
Contact Detail:
Morgan Spencer Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the rail industry or data engineering roles on LinkedIn. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ETL pipelines, APIs, or any relevant projects. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process when solving problems, as collaboration is key in this role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, especially with ETL pipelines and cloud platforms. We want to see how your skills align with the role, so don’t be shy about showcasing your projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the role and how your background makes you a great fit. We love seeing genuine enthusiasm for the rail industry and data challenges.
Showcase Your Technical Skills: When filling out your application, be sure to mention specific tools and technologies you’ve worked with, like Kafka or AWS. We’re keen on seeing your hands-on experience, so don’t hold back!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Morgan Spencer
✨Know Your Data Tools
Make sure you brush up on the data tools mentioned in the job description, like Kafka and dbt. Be ready to discuss your experience with these technologies and how you've used them to build ETL pipelines or handle data at scale.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data challenges in the past. Think about specific projects where you translated real-world problems into technical solutions, as this role is all about solving operational challenges in the rail industry.
✨Emphasise Collaboration
Since this role involves working closely with engineers, consultants, and project managers, be ready to talk about your experience in agile teams. Share examples of how you've contributed to sprint planning or participated in code reviews to highlight your collaborative spirit.
✨Stay Curious and Up-to-Date
Express your enthusiasm for learning new tools and trends in data engineering. Mention any recent tech talks or internal learning sessions you've attended, as this shows you're proactive about your professional growth and keen to contribute to the team's knowledge.
