Analytics Engineer, Payments Intelligence

Vinteden·Berlinmid

En corto

→Ingeniero de análisis enfocado en inteligencia de pagos para el nuevo servicio Vinted Pay.
→Diseñas y mantienes pipelines y modelos de datos para soportar decisiones estratégicas en pagos.
→Proyecto verde (greenfield) con alto impacto, trabajando en un servicio de pagos que se está construyendo desde cero.

Fluency in English is required for collaboration across international teams.

En ~1 minuto te damos: quién te entrevista, las preguntas probables con respuestas desde tu CV, y tu CV adaptado a esta vacante. Gratis, sin tarjeta.

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¿Qué piden?

✓Experiencia en construcción de pipelines de datos confiables y escalables.
✓Habilidades sólidas en SQL y Python para transformación de datos.
✓Capacidad para traducir necesidades de negocio en soluciones de datos.
✓Conocimiento en arquitectura de datos (data modeling, ETL/ELT).
✓Colaboración estrecha con equipos de producto e ingeniería.
✓Experiencia en entornos de datos cloud (GCP/AWS/Azure).

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

SQLPythonGCPAirflowBigQuerydbtLookerGitDockerKubernetes

¿A quién escribirle en Vinteden?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

Brief info about Vinted 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. Information about the position 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. In this

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