Analytics Engineer - Finance

Mews is building the operating system for modern hotels. Thousands of properties run their entire business on Mews - from reservations and revenue to payments and guest experience - all connected through a unified, guest-first data model.The roleFinance is at the centre of Mews’ next phase of growth. As the company scales toward IPO and expands internationally, Finance needs to shift from reactive, manual processes to strategic, data-driven operations. You’d build the analytical infrastructure that makes that possible. You’d design and develop data pipelines, models and features that give Finance leaders visibility into what’s happening across the business right now and what comes next. Your work unlocks month-end closes in five days instead of eight, automates manual GL and AR reconciliation, and gives the company the financial foundations it needs for IPO compliance and scale. This is greenfield work. Modern stack (DBT, Databricks, Python). High impact. Genuine autonomy.What you'll be doingBuild production-ready ETL/ELT pipelines and analytical solutions using DBT, Databricks and SQLDesign scalable data models that surface real-time insights for Finance leadership and operationsChampion data quality and testing practices; validate work before it reaches decision-makersWork directly with Finance leadership to translate priorities into technical solutionsShape the technical roadmap and advocate for modern data practices as the domain scalesWhat we're looking for3+ years building and optimising ETL/ELT pipelines in productionProficiency in SQL, Python and DBT (or equivalent modern data transformation tools)Experience with Databricks, Snowflake or similar cloud data platformsStrong grasp of data modelling, analytics architecture and the trade-offs between approachesComfort working autonomously, breaking down ambiguity, and managing priorities without constant directionWhy nowFinance is underinvested in systems. That's changing. The team is growing, the stack is modern, and the work is genuinely high-impact - directly supporting IPO readiness and international expansion. You'd be building from foundations rather than inheriting legacy systems.LocationEU-based (Czech Republic, UK, Spain or France)#J-*****-Ljbffr

3+ years building and optimising ETL/ELT pipelines in production Proficiency in SQL, Python and DBT (or equivalent modern data transformation tools) Experience with Databricks, Snowflake or similar cloud data platforms Strong grasp of data modelling, analytics architecture and the trade-offs between approaches Comfort working autonomously, breaking down ambiguity, and managing priorities without constant direction

Finance is underinvested in systems. That's changing. The team is growing, the stack is modern, and the work is genuinely high-impact - directly supporting IPO readiness and international expansion. You'd be building from foundations rather than inheriting legacy systems.