Analytics Engineer, Payments Intelligence

Our mission is to make second-hand the first choice, and we're looking for people who want to help us get there. Every day, we work together to help our members buy and sell pre-loved clothing and lifestyle items, giving each piece a second life – or even a third.
The Vinted Group is made up of three business units that support this mission:

Vinted Marketplace is Europe’s leading platform for second-hand fashion and a go-to destination for all kinds of pre-loved items, with a growing range of categories. Our platform connects millions of members across 20+ markets, helping great items find a new life.

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. 

In this role you will become a part of the Payments Intelligence team in Vinted’s Payments business unit. This team consists of a mix of Analytics Engineers, Decision Scientists and Data Scientists and works together with the product and engineering teams in the business unit as well as other teams across the whole DSA function on cross-domain topics. The Payments business unit consists of two domains: Marketplace Payments and Vinted Pay. Marketplace Payments is responsible for everything that is needed to make it possible to pay for items on Vinted while Vinted Pay is a brand new payment service provider that we are building. Your work will be mainly focused on Vinted Pay which is a greenfield project with many analytical engineering challenges and opportunities but as the Payments Intelligence team works on the business unit level you will also have projects related to other topics related to payments.

Within the Data Science & Analytics (DSA) function we have three distinct roles. We believe that each role can make a similarly sized business impact in different ways and therefore our salary ranges are the same for all three roles. To understand your role within DSA context better, here are brief descriptions of each role we have in the department:

• Analytics Engineers are responsible for data curation – translating data needs from stakeholders into architecting, building and maintaining efficient & reliable data models and pipelines.
• Decision Scientists are responsible for actionable insights, identifying and sizing opportunities, and automated tools that increase the quality of product and business decisions by applying statistical methods and data-driven decision making.
• Data Scientists are responsible for the identification of algorithmic opportunities, ensuring those opportunities are addressed in an optimal fashion and design, development and maintenance of production-grade statistical and machine learning algorithms.

• Design, build and maintain analytics engineering systems including but not limited to data ingestion, data models, pipelines, reporting automation and data products
• Work with colleagues and stakeholders in the Payments business unit and across the company to gather requirements and implement solutions for data projects
• Continuously learn to be a better Analytics Engineer and help your colleagues by upholding high professional standards and sharing your knowledge
• Have the opportunity to work with your colleagues in the Engineering organization or other DSA colleagues in other business units, to attend and present on knowledge sharing sessions and to participate in company- and function-wide initiatives

• Experience as Analytics Engineer, ETL Developer, Data Engineer or similar role
• Proficient in SQL - able to write SQL code which is easy to understand, simple to troubleshoot and is highly performant
• Familiarity with another programming language e.g. Python, Java, Scala
• Experience with analytics engineering tools and services (DBT, BigQuery, Snowflake, Airflow, etc.)
• Familiar with data modelling, data access and data storage techniques
• Strong communication & collaboration skills - able to build and maintain multi-functional relationships with various teams across the business as well as translate business needs into technical solutions
• Attentive to detail
• Excellent written and spoken English
• Advantage: working experience in cloud environment, for example GCP or AWS
• Advantage: experience with payment processing or in general anything FinTech

• 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

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!

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