ML Data Engineer — Scalable Pipelines & Feature Stores

Trainline; Greater London; Hybrid; GBP 60,000 - 68,000; Full time

Benefits offered by this job

Private healthcare

Dental insurance

Work from abroad policy

EV scheme

Festive time off

Family-friendly benefits

Job summary

Trainline is seeking an Embedded Data Engineer in ML to design scalable data pipelines, feature stores, and datasets that power machine learning workloads. You’ll deploy cloud-native apps on AWS and collaborate with ML Engineers and Data Scientists to deliver high-quality data for model training and analytics.

Join a diverse, hybrid team with strong learning culture, focusing on observability, CI/CD, and modern data tooling to deliver impactful data products across the business.

Qualifications

• Proven experience building data pipelines for ML workloads and feature engineering.
• Strong knowledge of Python and SQL for data processing and analytics.
• Experience with cloud data warehouses and data modelling in the cloud.
• Hands-on with Spark and Airflow in a cloud environment (AWS).
• Familiar with real-time and batch data workflows and orchestration patterns.
• Nice-to-have: Ray or distributed training frameworks; Parquet/Iceberg formats.
• Experience with Infrastructure as Code (Terraform) and containerisation (Docker).
• CI/CD experience (Jenkins or GitHub Actions) in production data systems.

Responsibilities

• Design and build scalable data pipelines, data models, and feature stores for ML workloads.
• Deploy and maintain cloud-native data applications on AWS with CI/CD pipelines.
• Maintain data pipeline quality, performance, and observability in production.
• Collaborate with ML Engineers and Data Scientists to build reliable datasets for ML use cases.
• Work with Data Engineering and Analytics communities to share best practices.

Skills

Python

SQL

Spark

Airflow

Terraform

Docker

Jenkins

GitHub Actions

AWS

Tools

DBT

Parquet

Iceberg

Kubernetes

Snowflake

Job description

Trainline is seeking an Embedded Data Engineer in ML to design scalable data pipelines, feature stores, and datasets that power machine learning workloads. You’ll deploy cloud-native apps on AWS and collaborate with ML Engineers and Data Scientists to deliver high-quality data for model training and analytics.

Join a diverse, hybrid team with strong learning culture, focusing on observability, CI/CD, and modern data tooling to deliver impactful data products across the business.