DATA ENGINEER

Data Engineer

Contract Type: Permanent
Location: London
Region: London
Sector: Physical Asset Management
Salary: Competitive, negotiable with possible equity in the medium term

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 transformations 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

• 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.

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