Analytics Engineer, Revenue, Purchase & Order

Vinted Go enhances the shipping experience with a vast network of over 500,000 pick-up and drop-off points, partnering with more than 60 carriers across Europe, with added services like item verification for peace of mind on high-value pieces.

Vinted Pay is the newest part of the Vinted Group, dedicated to bringing secure, reliable payments to buyers and sellers across Europe. Seamlessly integrated into the Vinted app, it helps keep every transaction safe, efficient, and easy for our members.

Founded in 2008 in Lithuania, Vinted began as a way for friends to find new homes for clothes they no longer needed. In 2019, we became Lithuania's first unicorn! Today, our headquarters remain in Vilnius, and we've grown with offices across Europe, supported by a team of over 2,000 people.

Information about the position

We are looking for an Analytics Engineer to join our Revenue, Purchase & Order Analytics Engineering team.

The area sits at the heart of some of the most critical customer journeys and commercial systems across Vinted’s Marketplace Business Unit, spanning Revenue (pricing and advertising), Purchase (inquiries and checkout), and Orders (transactions and fulfilment). Together, these domains create a rich, high-volume, and deeply interconnected data ecosystem.

As an Analytics Engineer, you’ll work at the intersection of data, engineering, and product, building trusted data products that power business and product decision-making across these domains.

In this position, you’ll

• Build scalable data products: Design, develop, and evolve reliable, cost-efficient data products and pipelines that power analytics and machine learning use cases across the domains.
• Build quality in by design: Embed automated testing, validation, and quality controls throughout the data lifecycle to ensure data remains accurate, consistent, and complete.
• Strengthen observability: Improve monitoring and alerting to detect and address issues before they impact downstream consumers.
• Own production reliability: Take end-to-end ownership of production data systems, from investigating incidents and diagnosing root causes to implementing durable fixes that prevent recurrence and improve long-term resilience.

Who you’ll work with:

• Revenue, Purchase & Order Analytics Engineering: Join a talented and driven team of 7+ Analytics Engineers, working across interconnected domains and tackling complex, high-impact data challenges.
• Data & Decision Scientists: Work closely with Data Scientists and Decision Scientists to build trusted data foundations that enable better business and product decisions.
• Engineering, Product & Business: Partner with Backend Engineering, Product, and Business teams to understand their needs, shape technical requirements, and translate them into well-designed, trusted data solutions.
• The Analytics Engineering Guild: Be an active member of Vinted’s 40+ member AE Guild, benefiting from shared tooling, engineering standards, and knowledge across domains. You’ll also have opportunities to contribute to “side quests” that improve engineering practices, tooling, and reusable capabilities.

About you

• Experience working as an Analytics Engineer, Data Engineer, or in a closely related data role.
• Strong SQL and data warehousing fundamentals, with the ability to build clean, performant, and maintainable data solutions.
• Hands-on experience with dbt or a similar data transformation framework, building well-structured and tested data models.
• Experience working with a cloud data warehouse such as BigQuery, Snowflake, Redshift, or similar.
• A solid understanding of data modelling principles and their application to real-world analytical problems.
• Familiarity with workflow orchestration tools such as Airflow, Dagster, or similar.
• Comfortable working with high-volume, business-critical data, balancing a high bar for quality and reliability with a pragmatic bias for action.
• Strong written and verbal communication skills in English, with the ability to clearly explain technical concepts and trade-offs to both technical and non-technical audiences.

Work perks

• The opportunity to benefit from our share options programme
• 30 days of paid annual leave
• Newest MacBook models
• Confidential Employee Assistance Program (EAP) for you and your family
• Home office support: we provide IT workstation equipment and a personal budget of up to €540 for home workplace furniture
• Lunch benefit per your workday
• Frequent team-building events
• A personal monthly budget for shopping on Vinted
• Access to a discounted gym membership plan
• Pension Plan with Vinted matching 150% of your chosen contribution
• Supplemental Private Health Insurance
• Life and Disability insurance
• A subsidised Deutschlandticket for your commute to the office by public transport
• A dog-friendly office

Working at Vinted

Workation policy

Better balance holidays with workdays by working remotely! Up to 90 days per year in the EU, of these, 21 days can be spent globally. For non-EU citizens, it's 21 days worldwide. This can be combined with time off for vacation or personal time.

Individual learning budget

Each year, you’ll be given a learning budget (starting at €3,000), and a total of up to 10 working days over a 2-year period to support your personal and professional development.

Hybrid work

Our hybrid model, with 2 recommended office days a week, gives you and your team the flexibility to decide if and when you want to work from home, and when to catch up in person.

Equal opportunity

We welcome applications from everybody, regardless of your background, identity, or life experiences. Job openings come with guides, not checklists. If you’re excited about a role, but don’t identify with every point in the ‘About you’ section, apply anyway – you might still be the perfect match!

The annual gross salary range for this position is:

€61.200 — €82.800 EUR

Wir zeigen einen Auszug und einen Link je Anzeige, und den vollen Text, wenn die Quelle es erlaubt. Genannte Marken und Logos gehören ihren Inhabern.

Veröffentlicht am 01. Nov. 2026

Veröffentlicht am 01. Nov. 2026

Quelle: Statistisches Bundesamt (Destatis), Tabelle; dl-de/by-2-0; eigene Berechnung