Analytics Engineer - Finance

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 SQLCreate 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 modelling and analytics architecture

Comfort working autonomously and managing priorities with ambiguity; ability to break down complex problems

Demonstrated commitment to data quality, testing and accuracy; take pride in work that's been thoroughly validated AI Fluency Level 3:
In this role, you'll redesign how Finance approaches data discovery and analysis using AI—not just automating your own work, but building patterns and tools that shape how the whole team questions data and validates insights. You'll use AI to accelerate model development and testing, but critically, you'll actively question what it produces and know when to push back. You've built processes others follow;

here, you'll do that with AI as a core enabler.

For more information on AI fluency at Mews, please refer to AI Fluency at Mews: A Comprehensive Guide for Candidates on Confluence.

Nice to have

Experience with data visualisation tools like Power BIBackground working with regulated or governed data Experience scaling analytics in fast-growing startups or scale-ups Spain
46.000—65.000 EUR Czechia
867 000 Kč— Kč CZKUK
49,500—55,500 GBPFrance $54,500—$65,000 USDPay Transparency at Mews Salary ranges are provided in good faith and reflect current market conditions and internal pay structures. Final compensation may be adjusted based on funding, budget constraints, or exceptional…