As an Analytics Engineer in the newly formed Vinted Go Finance Analytics Engineering team, you will design, build, and maintain the financial data models and pipelines that power accurate cost controlling, invoicing reconciliation, and financial reporting across our expanding logistics network.

Vinted Go handles hundreds of millions of parcel shipments across Europe, the US, and Australia, working with dozens of carriers. This role operates where logistics meets finance: turning complex, high-volume shipping and invoicing data into reliable, auditable, and automated datasets.

Who you’ll partner with:

• Vinted Go Financial Operations & Group Financial Reporting - you will learn about financial reporting and controlling requirements and use that knowledge to deliver trusted data for monthly closing, carrier invoice verification, and cost-per-parcel analysis.
• Fellow Analytics Engineers in Vinted Go Finance - you will collaborate closely on pipeline ownership, code reviews, and shared data marts.
• Vinted Analytics Engineering Guild (40+ colleagues) - you will benefit from shared best practices, reusable dbt/Python packages, and learning from cross-domain colleagues; and, conversely, contribute back to the guild.

You will report to the Team Lead for Vinted Go Finance Analytics Engineering.

• Build and maintain scalable financial data models in BigQuery and dbt that transform raw operational and carrier invoicing data into trusted, finance-ready datasets.
• Implement robust automated data quality controls (dbt tests, reconciliation checks, anomaly detection) to guarantee data accuracy and consistency.
• Improve pipeline monitoring and observability (freshness, volume shift detection, schema drift) to identify and resolve data issues before they impact stakeholders.
• Take active ownership of production reliability by investigating pipeline incidents, diagnosing root causes, and applying permanent fixes.
• Collaborate closely with Finance and FinOps stakeholders to translate business requirements and accounting rules into clear, well-documented technical specifications and metrics.
• Contribute to our shared Looker assets (models and dashboards) to enable self-service exploration for finance teams.

• Experience working as an Analytics Engineer, Data Engineer, or in a closely related data role building production-grade data pipelines.
• Strong SQL skills, with a focus on writing clean, readable, and performant queries.
• Hands-on experience with dbt and version control (Git), following modular modeling and testing practices.
• Good grasp of core data modeling concepts (dimensional modeling, star schemas, handling slowly changing dimensions, incremental processing).
• Strong communication skills in English, with the ability to discuss trade-offs, explain technical concepts to non-technical stakeholders, and document data models clearly.
• Pragmatic problem-solving mindset: you care about data correctness, auditability, and building solutions that are maintainable over time.

Nice to have (bonus points, not requirements):

• Familiarity with the broader stack: Google Cloud Platform (BigQuery), Apache Airflow, Python, Looker.
• Previous exposure to financial data concepts (e.g., invoice reconciliation, revenue/cost allocation, general ledger, accounting periods).

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

• The opportunity to benefit from our share options programme
• 25 working days of holiday
• Access to all the tools & tech needed for work
• Home office support: we provide IT workstation equipment and a personal budget of up to €540 for home workplace furniture
• Private health insurance
• Confidential Employee Assistance Program (EAP) for you and your family
• Frequent team-building events
• A personal monthly budget for shopping on Vinted
• A dog-friendly office
• In Vilnius office: gym & in-house meals at friendly prices
• In Kaunas office: a monthly lunch allowance, and a once-a-week provided in-house lunch and breakfast

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!