Senior Scala Engineer - Data Platform
London, United Kingdom
Trainline
Great journeys start with Trainline. Find out more about how we're changing the future of travel, and the part you could play in it.Company Description
We are champions of rail, inspired to build a greener, more sustainable future of travel. Trainline enables millions of travellers to find and book the best value tickets across carriers, fares, and journey options through our highly rated mobile app, website, and B2B partner channels.
Great journeys start with Trainline đ
Now Europeâs number 1 downloaded rail app, with over 125 million monthly visits and ÂŁ5.3 billion in annual ticket sales, we collaborate with 270+ rail and coach companies in over 40 countries. We want to create a world where travel is as simple, seamless, and affordable as it should be.
Today, we're a FTSE 250 company driven by our incredible team of over 1,000 Trainliners from 50+ nationalities, based across London, Paris, Barcelona, Milan, Edinburgh, Berlin, Madrid, and Brussels. With our focus on growth in the UK and Europe, now is the perfect time to join us on this high-speed journey!
Job Description
đ» Senior Data Engineer đLondon (Hybrid, 40% in office)Â đž ÂŁSalary + Benefits
Introducing Data Engineering at Trainline đÂ
Data Engineering is essential to how we unlock the value of data at Trainline. Our mission is to liberate Trainline data and delight customers with great data products built on a frictionless, modern data platform. Our data products include machine learning models that add real value to the customer journey, streaming data applications that personalize the customer experience in real time, dashboards that drive deep business and customer insight and intuitive and efficient data marts and metrics built on our modern data lakehouse.Â
As a Senior Data Engineer (Scala), you will be part of a cross-functional data product team working alongside data scientists, machine learning engineers and BI engineers. Our data product teams are deeply embedded in the business so your work will have high impact by either drive key business decisions, provide deep customer insights or by adding intelligent machine learning experiences right in the core of our customer journeys.Â
We use an agile delivery playbook that encourages incremental and iterative delivery, aims to release value early and often, measure the impact of work and using hypotheses to ensure we are solving real customer problems. Our data platform is a modern, cloud-native, lake house using best-of-breed technologies and partners, all based on the AWS public cloud.Â
We empower our Data teams and give engineers high levels of autonomy and freedom to innovate. We encourage continuous learning with clear career progression plans, innovation/hack days and training opportunities such as DataCamp.Â
As a Senior Scala Data Engineer at Trainline, you will... Â
- Use cutting-edge Data technology to deliver world-class data products using a combination of streaming technologies, machine learning and automated data pipelines. Â
- Work in self-organised, cross-functional data teams alongside machine learning engineers, BI engineers and product managers.Â
- Drive continuous improvement to the software engineering and agile working practices of the team.Â
- Contribute to the Technical / Architecture direction of the team.Â
Qualifications
We'd love to hear from you if you...đ Â
- Thrive in a diverse, open and collaborative environment where impact is as valuable as technical skill
- Have excellent knowledge of Scala and the JVM ecosystem
- Possess strong understanding of functional programming paradigms and a willingness to adopt other languages (not only JVM languages)Â
- Have consistent background in software development in high volume environments
- Have a pragmatic and open-minded approach to achieving outcomes in the simplest way possible
- Have worked with stream processing technologies (Kafka, Storm, AWS Kinesis, etc)
- Have experience with AWS services especially EMR, ECS, EKS.Â
- Have an obsession with software quality, Dev Ops and automationÂ
- Work well in lean, agile, cross-functional product teams using Scrum and Kanban practices
- Are a good communicator and comfortable with presenting ideas and outputs to technical and non-technical stakeholdersÂ
Our technology stack đ»Â
- Python
- Scala and the JVM
- Kafka, Kafka Streams and KSQL
- AWS, S3, Parquet, Iceberg, Glue and EMR for our Data LakeÂ
- Terraform and DockerÂ
- Elasticsearch and Dynamodb Â
- Spark and AirflowÂ
- Trinio (Starburst) and Presto (Athena)Â
- ML Flow and popular Python machine learning and analysis librariesÂ
The interview process đÂ
- Recruiter Call (30 mins)
- Meet the manager (30Â mins)
- Technical discussion with x2 Engineers (60 mins)
- Meeting a cross-functional team member (30 mins)
Additional Information
Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy, 2-for-1 share purchase plans, extra festive time off, and excellent family-friendly benefits.
We prioritise career growth with clear career paths, transparent pay bands, personal learning budgets, and regular learning days. Jump on board and supercharge your career from day one!
Our values represent the things that matter most to us and what we live and breathe every day, in everything we do:
- đ Think Big - We're building the future of rail
- âïžÂ Own It - We focus on every customer, partner and journey
- đ€ âTravel Together - We're one team
- â»ïžÂ Do Good - We make a positive impact
Interested in finding out more about what it's like to work at Trainline? Why not check us out on LinkedIn, Instagram and Glassdoor.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index đ°
Tags: Agile Airflow Architecture Athena AWS CX Data pipelines Docker DynamoDB ECS Elasticsearch Engineering Kafka Kanban Kinesis Machine Learning ML models Parquet Pipelines Python Scala Scrum Spark Streaming Terraform
Perks/benefits: Career development Equity / stock options Startup environment
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.