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# Data Engineer

- **Company:** The Trainline
- **Location:** Greater London, UK
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Airflow, Amazon Web Services, Business Intelligence Development, Code Review, Directed Acyclic Graph (Directed Graphs), Information Engineering, Data Mart, Data Security, Github, Identity and Access Management, Python (Programming Language), Scrum Methodology, SQL Databases, Apache Spark, Build Management, Data Lakes, Terraform, Data Pipelines, Jenkins
- **Published:** August 30, 2026
- **Apply:** https://www.collegerecruiter.com/job/2815455673-data-engineer

## About the Role

* Proven experience as a Data Engineering using SQL and Python
 * Previous experience with data lakes in AWS, Glue Catalog and Athena (or equivalent)
 * Good experience with DBT
 * Capable of using popular data modelling tools to create a diagram of proposed tables to enable discussion
 * Good communicator and comfortable with presenting ideas and outputs to technical and non-technical users
 * Worked on Apache Airflow before to create DAGS
 * Ability to work within Agile, considering minimum viable products, story pointing and sprints

## Description

At the heart of our Data Team, Data Engineers play a pivotal role by creating pipelines and tables that power impactful dashboards, enable self-service analytics, and support innovative machine learning models and real-time data products.

As a Data Engineer, you will be involved in engineering pipelines that will drive key decisions and give data science powerful datasets to enable and drive new business insights.

Data Engineers work alongside BI Developers and Data Scientists in cross-functional teams with key impacts and visions. As a department, we strive to give our Data Engineers have high levels of autonomy and freedom to innovate and continually refine their technical and soft skills with clear progression plans and training opportunities with Data Camp!, * Be key to making our data lake more accessible and insightful breaking down the barriers to access by working on new data marts and designing data models that even the most basic SQL users can use

 * Build data pipelines with Spark or DBT
 * Use SQL to transform data into meaningful insights
 * Build and deploy infrastructure with Terraform
 * Implement DDL, DML with Iceberg
 * Do code reviews for your peers
 * Orchestrate your pipelines with DAGs on Airflow
 * Participate in SCRUM ceremonies (standups, backlogs, demos, retros, planning)
 * Secure data with IAM and AWS Lake formation
 * Deploy your changes with Jenkins and GitHub actions


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