Python Data Engineer

The 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.

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.

Key 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.

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.