Area Lead Analytics Engineer

Vinteden · Berlinsenior

En corto

▸Lider técnico en ingeniería de datos para dominios clave (Ingresos, Compras, Pedidos).
▸Enfocado en arquitectura escalable, modelos de datos estandarizados y calidad operativa del ecosistema de datos.
▸Rol IC con impacto estratégico, no de gestión, apoyando múltiples equipos con estándares técnicos.

Fluent English (written and spoken) required

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.

¿Qué piden?

✓Experiencia comprobada en ingeniería de datos a gran escala.
✓Dominio de modelos de datos y arquitectura de pipelines confiables.
✓Habilidades avanzadas en SQL y transformación de datos.
✓Experiencia con infraestructura en la nube (AWS/GCP/Azure).
✓Capacidad para liderar técnicamente sin gestión directa.
✓Enfoque en calidad, mantenibilidad y observabilidad de datos.

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

SQLPythonAirflowdbtSparkKafkaAWSGCPDockerGit

¿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 We are looking for an Area Lead Analytics Engineer to provide strategic technical leadership and shape the long-term direction of analytics engineering across the Revenue, Purchase, and Orders domains. In this role, you will act as a technical lead across multiple domains,helping build a scalable, reliable, cost-efficient, and future-proof data ecosystem. This is a highly technical Individual Contributor role for someone who enjoys balancing hands-on engineering with strategic architectural leadership. You will define architectural standards, strengthen data modeling practices, reduce systemic complexity, and ensure that data products and pipelines are built for sustainable evolution. In addition, you will have the opportunity to drive strategic technical change and consistency that scales in the wider data science and analytics function. You will work with a talented team of analytics engineers, Data Scientists, Engineering Managers, Product Managers, and other technical stakeholders and will sit at the intersection of hands-on technical leadership, architectural governance, strategic direction-setting, and cross-domain enablement. In this position, you’ll • Set the long-term technical direction for analytics engineering across the Revenue, Purchase, and Orders domains. • Identify key intersections across Revenue, Purchase, and Orders, ensuring they are reflected consistently in data models and architecture. • Own architectural integrity, data modeling standards, reliability, and operational quality across the area. • Act as a central technical point of contact for cross-domain initiatives, helping teams align on technical decisions and priorities. • Create reusable patterns, shared standards, and a common design language for analytics engineering across domains. • Drive DSA-wide improvements in data product quality, maintainability, documentation, ownership, observability, and operational excellence. • Reduce and govern technical debt

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