Head of Data (Pricing & Revenue Intelligence)
Confirmed on the employer's own hiring board on Oct 30, 2026. First seen by Alion on Oct 26, 2026.
Amenitiz was built by hoteliers, for hoteliers. Today, more than 15,000 independent hotels across Europe trust us to run their business, and our mission hasn’t changed: give them the technology big chains take for granted, so they can grow on their own terms.
Now we want data to be the reason they earn more. As Head of Data, you’ll own our pricing and revenue intelligence: the strategy, the platform, the team, and the products you build with our Product Managers and Designers.
This isn’t a BI role: no request queue, no dashboard factory. We’re looking for someone who thinks about revenue before dashboards, has shipped data products that measurably moved a business, and still writes the code. If that’s you, we’d love to meet you.
Your missions
Turn our data into revenue for hotels. Understand what hoteliers do on the platform and what it produces, learn from it across thousands of similar hotels, and turn that into recommendations and actions inside the product. Recommendations a hotelier without a revenue manager will understand, and trust enough to switch on. Start where the value is highest, ship, measure, widen.
Show hoteliers what it earns them. Make the impact of what we build measurable and visible to the hotelier in the product, not only in our internal reports. Rigorously, at platform level, so the number holds; and honestly, hotel by hotel, against what a comparable hotel would have earned without us. Measurement rules are set before a feature launches and signed off by the CPO, so results are never graded against a better design found afterwards.
Shape the revenue products with Product. Co-own the roadmap for the products where data drives the outcome. Define what data and models they run on, and make sure every revenue feature ships with a measurable hypothesis and a way to learn from the result.
Run the data foundation without becoming it. Warehouse, pipelines, instrumentation, company reporting and self-serve analytics keep running, with clear standards and service levels, owned by your team. The foundation serves people and our AI agents alike: one definition per metric, built so an agent can answer a question as reliably as an analyst can. You own the company's metric definitions and are the senior voice on data in the leadership team. You hold clear standards for the quality, access and privacy of guest and hotel data across four countries.
Lead and grow the team. A small team of data engineers and data analysts that already stays at the front of AI and ships to customers. Hire, set growth paths, give feedback, build an environment the team thrives in. Lead by building alongside them.
Stay hands-on. Write SQL and Python, ship models, debug pipelines, review code. On a team this size, you are one of its strongest builders.
What you'll work with. Everything runs on AWS: Redshift modelled with dbt, Airflow, Airbyte and Glue for ingestion, SageMaker for models, Cube as the semantic layer that serves dashboards and AI tools from the same definitions, and our own internal AI assistant and agent service on top. All of it is code, deployed from GitHub. You'll have opinions on what to keep and what to change.
How we'll measure success
Data-driven features in production with measured impact, not models in notebooks.
Measured revenue impact, measured with rigour across the platform, visible to each hotelier in the product, and a number the company can stand behind. Proven impact takes months to become significant, and we plan for that.
Adoption: the share of hotels that switch our recommendations and automation on, and keep them on.
Foundation reliability: reporting and pipelines run without you, with no single point of failure.
Team health: a stable, growing team with clear growth paths, shipping to customers every week.
About you
You've built products around data, not dashboards about it. You've shipped models, recommendations or pricing logic into a product that customers used, and you can show us the business result, including one that didn't work and why.
You're hands-on, and you still are. SQL, Python, modern data tooling, experimentation. You'd rather build than only review.
You've led a small data team in a startup. Data engineers and analysts, hiring, growth, standards and platform reliability on your plate, with a small budget and more ambiguity than process.
You measure honestly. You know when an A/B test is the answer and when it isn't, and you can measure impact when you can't randomise: matched controls, holdouts, synthetic controls. You'd rather report a smaller number you can defend than a bigger one you can't.
You think in customer impact. You judge your work by what it changed for the people using the product, and you're comfortable owning a revenue number.
You work AI-first. Agents, LLM pipelines and automation are part of how you and your team build.
Highly collaborative, with a track record of working closely with Product, Design, Engineering, leadership and customer-facing teams.
Experience in hospitality, travel, marketplaces, pricing and revenue management, demand forecasting or econometrics is a plus.
Fluent English required. Spanish, French, Italian or Portuguese are a strong plus.
Our offer
Stock options with a progressive vesting schedule
Comprehensive health insurance with Alan
25 days of holidays from day one, rising to 28 after your first year and 30 after two years
€10 a day for lunch through our virtual canteen, Kombo, every day you work from the office
Flexible benefits - save on meals, childcare, transportation, and training with our tailored remuneration options
Any book, purchased for you, plus access to a shared team library
An international team of 35+ nationalities based in one of Europe's leading tech hubs
Hiring process
A 30-minute call with Talent Acquisition.
A 60-minute conversation with the Chief Product Officer.
A management conversation about how you lead a team.
A case study on real (anonymised) data.
A final conversation with our CEO.
References, including a former direct report.