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Senior Data Engineer, Data Platform

2 months ago

London, Greater London, United Kingdom Trainline Full time

Job Description

Senior Data Engineer, Data Platform

Trainline is seeking a highly skilled Senior Data Engineer to join our Data Platform team. As a Senior Data Engineer, you will play a key role in designing, building, and maintaining our modern cloud-native data lakehouse.

About the Role

We are looking for a talented Senior Data Engineer to join our team and contribute to the development of our data platform. The successful candidate will have a strong background in data engineering, experience with cloud-native technologies, and a passion for delivering high-quality data products.

Key Responsibilities

  • Design and implement data pipelines using cutting-edge technologies such as streaming technologies, machine learning, and automated data pipelines.
  • Work closely with cross-functional teams, including data scientists, machine learning engineers, and product managers, to deliver world-class data products.
  • Drive continuous improvement to the software engineering and agile working practices of the team.
  • Contribute to the technical architecture direction of the team.

Requirements

  • Excellent knowledge of Scala and the JVM ecosystem.
  • Strong understanding of functional programming paradigms and a willingness to adopt other languages, not only JVM languages.
  • Consistent background in software development in high-volume environments.
  • Pragmatic and open-minded approach to achieving outcomes in the simplest way possible.
  • Experience with stream processing technologies, such as Kafka, Storm, and AWS Kinesis.
  • Experience with AWS services, especially EMR, ECS, and EKS.
  • Obsession with software quality, DevOps, and automation.
  • Good communication and presentation skills, comfortable presenting ideas and outputs to technical and non-technical stakeholders.

Our Technology Stack

We use a range of technologies, including Python, Scala, and the JVM, Kafka, Kafka Streams, and KSQL, AWS S3, Parquet, Iceberg, Glue, and EMR for our data lake, Terraform and Docker, Elasticsearch and DynamoDB, Spark, Airflow, Trino, Starburst, and Presto, Athena, ML Flow, and popular Python machine learning and analysis libraries.

The Interview Process

The interview process will consist of a recruiter call, a meeting with the manager, a technical discussion with two engineers, and a meeting with a cross-functional team member.