Data Engineer

• 08 October 2026
• 100%
• Indefinite duration
• Chiasso

Join lastminute.com, the European leader in dynamic travel. Benefit from an inclusive and innovative environment.

Tasks ##

• Manage the data model of your business domain.
• Collaborate with stakeholders on key KPIs.
• Establish validation rules to ensure data trust.

Skills ##

• Solid experience in data engineering and dimensional modeling.
• Advanced skills in SQL and query optimization.
• Practical knowledge of orchestration tools such as Airflow.

Data Engineer

• Full time
• Department: Data

Company Description

lastminute.com is the European leader in Travel Tech for dynamic holiday packages. It operates a portfolio of well-known brands such as lastminute.com, Volagratis, Rumbo, weg.de, Bravofly, Jetcost and Hotelscan.

Our mission is to lead the travel industry by leveraging technology to simplify, personalize, and enhance our customers' travel experience. Experts in driving online travel, we help our customers find and do "what makes them happy".

We continuously invest in talent that ensures our offering is closer to customer needs and keeps us at the forefront of technological evolution. More than 1,700 employees spread across our offices around the world develop our own products and services to power the entire traveler journey for millions of people.

At the heart of our culture is a commitment to inclusion, regardless of race, gender, age, sexual orientation, religion, gender identity or expression, and accessibility. We firmly believe in a space of equal opportunity, welcoming and celebrating the uniqueness of each of our employees. We value different lived experiences and respect different viewpoints, as we know that uniqueness drives innovation. We want to ensure that our employees reflect the global communities we help to travel.

lastminute.com N.V. is a company listed on the stock exchange under the symbol LMN on the SIX Swiss Exchange.

Job Description

What you will take on

The data model of your business domain. Entities, granularity, dimensional models, metrics, and definitions. You decide on the source of truth and the boundaries of the business domain. Definitions are treated as a product here: one owner, a documented definition, a single place where it is calculated, the same value everywhere it is consumed.

The relationship with stakeholders. You co-manage the set of KPIs that the company tracks: what we look at every week, how it is defined, and when it should change. You are expected to rephrase the question when the question is the problem. On smaller or continuous tasks, you agree on priorities directly with your stakeholders. On the broader roadmap, you set priorities with your manager, including what we can postpone or deprioritize.

Analysis, adapted to the business domain. The split between analysis and development depends on the domain you manage, and can evolve over time.

Trust in the numbers. You build validation and monitoring rules on your own models, so that data problems are detected before the data reaches a dashboard or a stakeholder. When a problem occurs, you manage it end-to-end: finding the cause, explaining the business impact, correcting it, and adding a test to prevent it from happening again.

Leverage beyond yourself. What you learn about your domain becomes reusable for the entire department - documented models, shared glossaries and AI context, automations.

Qualifications

What we are looking for

Essential

Solid and practical experience in data engineering, analytics engineering, or a similar role. We look at what you have built, not the number of years.

True mastery of dimensional modeling: granularity, keys, slowly changing dimensions, and the judgment to know when a model is semantically incorrect even if it works.

Advanced SQL and query optimization on a cloud or MPP warehouse. We use BigQuery and Vertica - you must be proficient in one of them, not necessarily both.

Practical experience with dbt for transformation and modeling, and comfort with orchestration (Airflow, Cloud Composer or equivalent).

Operational knowledge of a business domain and the ability to link data work to business outcomes rather than task execution.

Proven experience working directly with non-technical stakeholders: transforming a business question into a data requirement, presenting results, and challenging the brief when the data says otherwise.

Fluent English, written and spoken.

Strong assets

AI-assisted working methods (see below) - daily use of an agentic assistant for development and analysis, and the ability to write the context that makes it reliable. If you already work this way, you will be fast here and we will want you to shape how the rest of the department proceeds.

Python for automation and lightweight services.

Data contracts, test frameworks, or data observability tools.

Experience as a data point of contact embedded within a business team.

Semantic layers or metrics consumed by BI tools and AI agents.

Travel, OTA, marketplace, or other high-volume transactional business.

How we work with AI

Claude is part of the standard toolkit of this department, connected to our own sys