Data Engineer

What you will own

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

The relationship with stakeholders. You co-own the KPI set the business steers by: what we look at every week, how it is defined, and when it needs to change. You are expected to reframe the question when the question is the problem. On smaller or ongoing work, you agree priorities directly with your stakeholders. On the wider roadmap, you set priorities together with your manager, including what we can postpone or deprioritise.

Analysis, sized to the business area. The split between analysis and development depends on the business area you look after, and it can change over time.

Trust in the numbers. You build validation rules and monitoring on your own models, so that data issues are caught before the data reaches a dashboard or a stakeholder. When something goes wrong, you handle it end to end: find the cause, explain the business impact, fix it and add a test so it does not happen again.

Leverage beyond yourself. What you learn about your business area becomes reusable for the whole department — documented models, shared glossaries and AI context, automations

What we look for

Essential

• Solid, hands-on experience in data engineering, analytics engineering or a similar data role. We look at what you have built, not at the number of years.
• Real depth in dimensional modelling: grain, keys, slowly changing dimensions, and the judgement to know when a model is semantically wrong even though it runs.
• Advanced SQL and query optimisation on a cloud or MPP warehouse. We run both BigQuery and Vertica — you need to be strong on one of them, not both.
• Hands-on dbt experience for transformation and modelling, and comfort with orchestration (Airflow, Cloud Composer or equivalent).
• Working knowledge of a business area and the ability to connect data work to business outcomes rather than to task completion.
• A track record of working directly with non-technical stakeholders: turning a business question into a data requirement, presenting findings, and disagreeing with the brief when the data says otherwise.
• Fluent English, written and spoken.

Strong plus

• AI-assisted ways of working (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 quick here and we will want you shaping how the rest of the department does it.
• Python for automation and lightweight services.
• Data contracts, testing frameworks, or data observability tooling.
• Experience as the reference data person embedded in a business team.
• Semantic or metric layers consumed by BI tools and by AI agents.
• Travel, OTA, marketplace or another high-volume transactional business.

How we work with AI

Claude is part of the standard toolkit of this department, connected to our own systems, and it changes what we consider skilled work. Writing correct SQL is no longer the scarce part. Deciding what correct means, and building the context that lets both people and agents get it right, is.

In practice that means: agentic development as the default for SQL, dbt, Python and documentation, with normal engineering discipline around it; context written and maintained by you — instruction files, reusable skills, business glossaries, model documentation — because the quality of the output depends on it; agent-assisted data quality work with a human review gate wherever it feeds a business decision; and clear-eyed judgement about where these tools are unreliable in this specific business area.

We are not looking for prompt-writing as a job. We are looking for someone whose modelling and business judgement is worth multiplying.

Life of working in lastminute.com

Perks of working with us:

• An inclusive, friendly, and international environment (you’ll be working with colleagues from +10 countries and over 48 nationalities)
• Shorter working week (36h as full time), with a half working day on Fridays
• Flexible start and end of the working day
• Possibility to work from anywhere for a period of time per year defined according to local regulations

How we learn together:

• Fri-Yays: half a day on Friday morning with a no-meeting mandate and dedicated to deep work, personal growth, learning and training and/or focus time.
• Professional and managerial skills development training paths, access to e-learning platforms such as O’reilly, Udemy, Coursera (depending on the department), and to our internal platform offering bespoke training content

Other perks:

• 2 paid days off per year for volunteering purposes
• Occasional social events to foster …