Data Engineer

Data Engineer

Vacancy Information

• Location: London, UK
• Salary: Competitive
• Working Pattern: Hybrid, 3 days per week in the office
• Contract Type: Permanent
• Working Hours: Monday to Friday

At TTC, we are Enriching lives by connecting people and places.

For over 100 years, we’ve been bringing the world closer together by crafting journeys that create lasting memories, lifelong friendships and meaningful cultural connections. Across more than 70 countries and our award-winning brands, we design and deliver travel experiences that go beyond sightseeing - they change perspectives.

Behind every unforgettable journey is a passionate team making it happen. That’s where you come in.

Our Values

Five shared commitments shape how we work, and how we will work with you:

• Value Every Voice. We put people first.
• Act with Integrity. We do what is right.
• Explore Beyond Boundaries. We are driven by curiosity.
• Own the Outcome. We take responsibility for our decisions.
• Succeed Together. We have each other's backs.

The Role

This is a chance to help build the modern data foundations behind TTC's growing Data and AI capability. You will design and develop reliable pipelines and trusted data products across customer, booking, digital, marketing, commercial and operational data, enabling analytics, data science and better decisions across our global portfolio of travel brands.

You will work in a modern Snowflake-based ecosystem alongside senior engineers, data scientists, analysts and data product colleagues, turning complex data into accessible, reusable, high-quality assets. The platform is being actively developed and scaled, so you will learn quickly, see your work used and grow alongside strong engineers who are happy to share what they know. If you care about doing things properly and want room to develop, you will do well here.

What Will You Do?

• Build and maintain scalable, production-grade pipelines across customer, booking, digital, commercial and operational domains.
• Turn raw data into trusted, reusable and well-modelled products for Analytics, Data Science and AI.
• Develop solutions in Snowflake, SQL, Python and modern transformation tooling such as dbt.
• Build analytical models that give consistent views of customers, bookings, products and key entities.
• Implement automated testing, data quality controls, monitoring and observability across critical datasets.
• Apply modern engineering practice including Git, code review, automated testing and CI/CD.
• Monitor and optimise workloads for performance, scalability, resilience and cost.
• Work with senior engineers to apply reusable patterns and technical standards.
• Partner with Data Science, Insight and Data Product colleagues to translate needs into solid technical solutions.
• Investigate data quality and pipeline issues, find root causes and fix them properly.

About You

Essential

• Strong professional experience in data engineering or analytics engineering.
• Strong hands-on capability with SQL and Python.
• Experience with Snowflake or another modern cloud data platform.
• Experience designing and developing ELT and ETL pipelines in production.
• A good understanding of analytical and dimensional data modelling.
• Experience with dbt or comparable modern transformation tooling.
• Familiarity with Git, CI/CD, automated testing and data quality practice.
• A collaborative mindset and a genuine interest in building things well.

Desirable

• Experience with orchestration tools such as Airflow, Dagster, Prefect or Azure Data Factory.
• Experience working within AWS, Azure, GCP or another enterprise cloud ecosystem.
• Experience with complex customer, transactional, digital or behavioural data.
• Exposure to data security, governance, lineage and documentation practice.
• Curiosity about travel, hospitality or global consumer businesses.

Apply Now

If you want to build data foundations that thousands of colleagues and millions of travellers rely on, we would like to hear from you. Apply today, and tell us what you would want to build first.