Analytics Engineer - Finance

Job description

Help make the world more hospitable The hospitality industry is uniquely human, and it deserves technology that’s just as inspiring as the people behind it. At Mews, we’re transforming the industry with a platform that helps hotels run smarter, move faster and create better guest experiences. You’ll work with smart, curious people who care deeply about what they do. You’ll have autonomy and the trust to make good decisions and move quickly. And you’ll enjoy a real sense of purpose as you see the impact of what we’re building. If you’re motivated by ownership, curiosity and meaningful impact, and are driven to deliver consistent high performance, you’ll feel at home here. About the role Let's get into the specifics. It’s impossible to capture every nuance of a role – especially at a rapidly growing company like Mews – but if we had to distil it into a job description (which we do because this is a job description), it would be this: You'll be the founding analytics engineer in Finance, shaping our data infrastructure and analytical capabilities during a critical transformation. Your expertise in Python, DBT , SQL, and Databricks will drive operational efficiency, accelerate our month-end close, and deliver strategic insights that inform capital allocation and IPO readiness. This is a greenfield opportunity to own the analytics roadmap, work directly with Finance leadership, and build infrastructure that powers both scaling and compliance, all at a pivotal moment for Mews What you would do Design and develop analytical features that surface actionable insights for Finance leadership Build, optimise and maintain production-ready ETL/ELT pipelines using DBT, Databricks and SQL Create scalable data models and analytical solutions using modern data modelling techniques Build and champion data quality and testing practices; catch errors before they reach stakeholders Collaborate across Finance to translate business requirements into technical implementations Advocate for modern data practices and continuous improvement of the stack What you would bring Hands-on production experience building and optimising ETL/ELT pipelines (minimum 3 years) Proficiency in SQL and Python; strong experience with DBT or equivalent modern data transformation tools Experience with Databricks or similar cloud data platforms, or willingness to ramp quickly Strong understanding of data m…