Data Engineering Lead
Technology – Development
Trainline is an innovative, tech business with a mission to make travel as simple, seamless and affordable as possible. We’re proud to be Europe’s leading independent train and coach platform and rank among the highest-rated travel and ticketing apps globally. Today, we offer our customers travel to thousands of destinations in and across 45 countries in Europe and beyond. That’s more than £2.7 billion in ticket sales annually, and over 80 million visits to our apps and websites each month.
Our culture is central to our success. We’re driven to sustain our phenomenal growth from recent years, and this means we’re always working closely and collaboratively to turn our ideas into reality. It’s this sense of pace, innovating and improving pretty much everything we do, that makes Trainline so exciting and unique - we truly believe our work has a genuine impact and will change travel for the better.
The Data Engineering Team Lead will work on the development and implementation of our next generation data platform; creating secure personalisation and insight services backed by scalable & secure data stores that integrate data from purchases, click streams, indications of intent, external events, CRM data, Social etc.
This is an opportunity for an experienced Data Engineer to help build a world class data platform that positively impacts the lives of millions of rail users. Within Trainline you will play a key role in Data development and help drive best practices across the team.
What you'll be doing
- Work with Product Owners to understand requirements and prioritise feature development
- Define technical direction for the Data Engineering team
- Collaborate with Data Scientists to design and build solutions.
- Lead the engineering team to design, build and operate solutions;
- Own the impact that your team brings;
- Build a strong team culture, by leading through context and autonomy, not control.
What you'll bring
- Polyglot data-related programming languages (Python, Clojure, Scala, etc);
- Application tools and frameworks (Git, Docker, Terraform);
- Hadoop / Kafka;
- AWS data services (EMR, Athena, Redshift, Glue, Kinesis, etc);
- Agile methodologies.