Data Engineer

We’re an ambitious, remote-first travel scale-up, eager to grow our team with an exceptional Data Engineer. If you’re passionate about leveraging data to solve meaningful problems, enjoy creating scalable infrastructure, and have a love for the outdoors, this is the opportunity for you!

The Role

You’ll be our first dedicated Data hire, building on our strong foundations to take our capabilities to the next level. You’ll work closely with product, engineering, and business teams to refine our data pipelines, optimise tracking, and empower decision-making across the company.

From enhancing our DBT pipelines and maintaining our Redshift warehouse to improving tracking with Segment and other analytics tools, you’ll play a key role in making sure we can deliver exceptional experiences for our customers and valuable insights for our team.

This is a hands-on role that will see you own our data engineering processes while collaborating across teams to support a wide variety of data-driven initiatives, from reporting and analytics to the groundwork for machine learning models.

Why You’ll Love It Here

We’re driven by a shared passion for leveraging data to solve meaningful problems and unlock new opportunities. Reporting directly to the CTO, you’ll have the autonomy to shape our data strategy while collaborating closely with others who are equally invested in creating a data-driven culture that drives impactful decisions.

We embrace a culture of learning and improvement, constantly evolving how we work to suit the challenges we face. You’ll find a supportive, collaborative environment where ideas are valued, feedback is encouraged, and experimentation is part of our DNA.

Key Responsibilities

• Enhance and scale our data infrastructure: Build upon our existing DBT pipelines, Redshift warehouse, and Segment integration to ensure robust, scalable, and accessible data systems.
• Optimise event tracking and analytics: Improve tracking and customer insights using tools like Segment, PostHog, and GA4.
• Enable self-service data capabilities: Create data marts and user-friendly dashboards that empower teams to make informed, data-driven decisions.
• Collaborate with stakeholders: Partner with product, engineering, and business teams to understand data needs and deliver impactful solutions.
• Prepare for advanced analytics: Lay the groundwork for data science projects such as churn forecasting, dynamic pricing, and recommendation engines.
• Maintain data quality: Ensure all data pipelines, systems, and models are accurate, reliable, and performant.
• Deliver value through automation: Streamline reporting processes to provide clear, timely insights with minimal manual intervention.