We are looking for an Area Lead Analytics Engineer to shape the technical direction of analytics engineering across our Revenue, Purchase, and Orders domains.

The Revenue, Purchase & Orders area sits at the heart of some of the most critical customer journeys and commercial systems in Vinted’s Marketplace business unit. Its scope spans Revenue, including pricing and advertising; Purchase, including checkout and transaction flows; and the Orders lifecycle, from a successful purchase through order management and completion.

Together, these domains form a broad and highly interconnected data landscape. As Area Lead Analytics Engineer, you will help ensure that the underlying data foundations evolve coherently and at scale. You will work across domains to identify shared concepts and dependencies, address structural data and architectural challenges, and guide the area toward a more scalable, consistent, and sustainable data ecosystem.

This is a senior Individual Contributor role combining hands-on engineering with architectural leadership. You will partner closely with area and domain leads, define technical standards and reusable patterns, build scalable data products, and reduce systemic complexity as our data ecosystem grows.

Your impact will extend beyond the area itself. You will help raise engineering quality and consistency across the wider Data Science & Analytics (DSA) function, working closely with Analytics Engineers, Data Scientists, Decision Scientists, Engineering, Product, and Business teams.

• Set the long-term technical direction across Revenue, Purchase, and Orders.
• Design and build scalable, reliable, and cost-efficient data products.
• Identify cross-domain dependencies and ensure shared concepts are consistently represented in data models and architecture.
• Define standards for data modeling, semantic layers, event data, observability, reliability, and testing.
• Lead technical decisions for cross-domain initiatives and create reusable patterns and architectural guardrails.
• Drive improvements in data quality, maintainability, ownership, cost efficiency, and operational excellence across DSA.
• Partner with Engineering on event-driven and behavioral data, from event definitions and instrumentation to reliable downstream models.
• Mentor other ICs through technical guidance, design reviews, and code reviews.

You are a seasoned Analytics Engineer, Data Engineer, or technical IC with strong engineering fundamentals and a track record of creating impact beyond your own delivery.

We are looking for:

• Experience designing and operating production-grade data models, pipelines, and data products at scale.
• Strong expertise in SQL, data modeling, semantic layers, and transformation frameworks such as dbt.
• Experience with modern cloud data platforms and technologies such as BigQuery, Snowflake, Redshift, Iceberg, GCP, AWS, or Azure.
• Strong understanding of testing, lineage, data quality, observability, reliability, query performance, and cloud cost governance.
• Experience working with event and behavioral data, including event schemas, instrumentation, and translating them into reliable analytical models.
• Experience with orchestration tools such as Airflow, Dagster, or similar, and a practical understanding of event-driven architectures.
• Demonstrated ability to establish technical standards, reusable patterns, or architectural guardrails that improve how multiple teams work.
• Strong systems thinking, with the ability to identify dependencies, repeated patterns, architectural risks, and opportunities to simplify complex data ecosystems.
• Evidence of cross-team technical influence and impact at scale, whether through architectural change, scaling engineering practices, or raising the maturity of a data function.
• Ability to communicate technical trade-offs clearly, influence without formal authority, and mentor other ICs.
• Familiarity with ML-facing workloads, feature stores, and BI platforms such as Looker, Tableau, or Power BI is valuable.

This is a broad, cross-domain role, so it is likely to be the best fit for candidates who have had the opportunity to work across multiple teams, domains, or areas of a data organisation.

Experience within a single vertical can absolutely be valuable; for this particular role, we are especially interested in examples where you have also influenced shared architecture, technical standards, or ways of working beyond your immediate area.

This is also a business-facing analytics engineering role rather than a data platform engineering role. If your experience has primarily focused on building data platforms, infrastructure, or developer tooling, with limited hands-on experience designing business-facing data models, pipelines, and analytical data products, this role is unlikely to be the right fit.

Similarly, we would love to hear about situations where your impact has extended beyond the systems you personally delivered for example, by helping scale an analytics engineering function, introducing practices adopted by several teams, leading architectural change, or improving the reliability and maintainability of a broader data ecosystem.

Experience in marketplace or e-commerce, modern warehouse/lakehouse architectures, data mesh, or data products serving both analytics and ML workloads.

Studies show that women and members of underrepresented communities often apply for jobs only if they meet 100% of the qualifications. If you do not recognise yourself in all of the above, you might still be an excellent candidate. If this role excites you, we encourage you to apply.

• The opportunity to benefit from our share options programme
• 30 days of paid annual leave
• Newest MacBook models
• Digital mental and emotional health support and Employee Assistant Program (EAP)
• 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

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!