Data Engineering Manager
Summary
Leads the data engineering chapter at a travel tech company, balancing hands-on platform decisions with people leadership. Shapes event-driven and traditional data pipelines, orchestration, governance and data quality using cloud tools like Databricks, BigQuery and Spark to power analytics and AI-driven initiatives.
In this Data Engineering Manager role, you lead the data engineering chapter to build reliable, scalable data products powering analytics and AI-driven initiatives. You’ll balance hands-on platform decisions with people leadership, guiding event-driven and traditional data pipelines across the business. You’ll partner with product, analytics, and engineering stakeholders to ensure robust, well-governed data platforms. This is an opportunity to shape modern data movement at a remote-first travel tech company with a strong engineering culture.
Pay / Benefits- 25 days holiday plus birthday off
- Learnerbly learning platform and professional development
- Enhanced parental leave and family support
- Employee Assistance Programme and counselling
- SIP (Share Incentive Plan)
- Gym discount
- Lead and develop a team of data engineers to deliver high-quality work
- Shape ingestion and processing of both event-driven and traditional data sources
- Design and evolve the data platform, including pipelines, orchestration, observability, lineage, governance and data quality
- Collaborate with Product, Engineering, Analytics and Data teams to translate business needs into scalable data solutions
- Define and improve data engineering standards around testing, monitoring, deployment and reliability
- Make pragmatic technical decisions balancing delivery speed, platform quality and business value
- Foster a culture of technical curiosity, continuous improvement and strong engineering practice in the team
- Communicate technical concepts clearly to both technical and non-technical stakeholders
- Experience building, operating or leading cloud-based data platforms and production-grade data workflows
- Hands-on with data pipelines, data modelling, orchestration and cloud tools (Databricks, BigQuery, Spark)
- Experience with event-driven or streaming data patterns and traditional data environments
- Ability to design reliable, observable, well-tested data products trusted by diverse users
- Coaching or mentoring engineers and supporting career progression
- Strong communication and decision-making in fast-moving settings
- communication
- coaching and mentoring
- stakeholder management
- cloud-based data platforms
- data pipelines
- data modelling
