Hybrid Principal Data Engineer

at Trainline

• Job title: Principal Data Engineer
• Job type: Full Time
• Experience level: Lead
• Salary: £100,000 - £120,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: Airflow, Apache, AWS, Python, Ray, Spark, SQL
• Location requirements: Hybrid, London, United Kingdom

About the role

• Principal Data Engineer at Trainline shaping robust data foundations for AI and ML-driven products. Collaborate with cross-functional teams to ensure best practices in data engineering and ML.

Responsibilities

• Act as a technical authority across multiple teams, setting standards and patterns for data and ML‑adjacent infrastructure
• Embed with ML teams to design, build and evolve data platforms supporting AI and ML workloads
• Influence technical direction without direct line management responsibility
• Partner with Data Engineering teams outside of ML to build a community and share best practices and findings across all areas
• Identify systemic issues and proactively drive improvements across the data ecosystem
• Look for short term and strategic opportunities to enhance core platforms with new self-serve enablement features for ML and DE
• Partnering with MLEs to design data pipelines supporting model training, inference and experimentation
• Designing and reviewing architectures for ML‑ready data platforms
• Building and optimising data pipelines using SQL, Spark or Ray and Python
• Defining best practices for orchestration using Airflow or similar tools
• Supporting API‑driven and event‑based data access patterns
• Working with AWS infrastructure such as ECS, vector databases and Bedrock APIs
• Reviewing designs and code across teams to raise quality and consistency
• Coaching engineers through pairing, design reviews and informal mentoring
• Collaborating on innovative AI‑powered product features such as the Travel Assistant

Requirements

• Extensive experience as a Senior, Staff or Principal Data Engineer operating across teams
• Deep expertise in SQL and Python, with strong experience in Spark or similar tooling.
• Strong understanding of orchestration tools such as Apache Airflow
• Experience designing data platforms for ML and AI workloads
• A track record of introducing new technologies and practices, and handling ambiguity and multiple stakeholders.
• Hands‑on experience with AWS infrastructure (e.g. ECS, IAM, data storage, compute)
• Familiarity with vector databases and modern AI/ML APIs (e.g. Bedrock)
• Experience working closely with Machine Learning Engineers in production environments
• Strong system design skills and the ability to influence through technical leadership

Benefits

• Private healthcare & dental insurance
• Generous work from abroad policy
• 2-for-1 share purchase plans
• EV Scheme to further reduce carbon emissions
• Extra festive time off
• Excellent family-friendly benefits
• Career growth with clear career paths
• Transparent pay bands
• Personal learning budgets
• Regular learning days