Staff Data Engineer

Role Overview: We are looking for a Staff Data Engineer to join our growing Product & Tech team. In this role, you will help shape the evolution of our data platform and influence engineering decisions across multiple cross-functional teams. Your main goal will be to partner with us in designing and scaling our data platform, strengthening both our operational databases and analytical platform, and bringing quality software engineering practices to all our data products and pipelines. You’ll collaborate closely with the product team and backend engineers, and serve as a trusted partner to business stakeholders who depend on accurate, timely data to drive product decisions and company strategy. This role is ideal for someone with strong skills in Python and SQL, solid software engineering fundamentals, a background in data-intensive product or platform teams where they contributed to production data architectures and pipelines end to end, and the ability to succeed in a dynamic, outcome-focused environment owning the full data cycle from operational to analytical systems. Main responsibilities: Define and drive the technical vision for our data platform and architecture. Design scalable, reliable, and maintainable data solutions that support business growth. Establish and cultivate best practices around data architecture, modeling, quality, and engineering standards. Lead complex technical initiatives and make strategic architectural decisions across multiple teams. Partner with Product, Engineering, and business stakeholders to translate business needs into scalable data solutions. Mentor and support Data Engineers, fostering technical growth and knowledge sharing across the team. Drive continuous improvements that increase the scalability, reliability, and efficiency of our data platform. Main requirements: Proficiency in Python for data engineering: Building robust ETL/ELT pipelines, modular libraries, and tooling with strong testing and observability. Advanced SQL skills with PostgreSQL: Complex query design, performance tuning, indexing strategies, and a deep understanding of execution plans for both OLTP and OLAP workloads. Strong experience with dbt: Data modeling, testing, and documenting analytical datasets, managing environments, and structuring projects for scalability. Hands-on experience with Dagster (or similar orchestration tools): Designing assets/jobs, dependency graphs, scheduling, monitoring, and incident handling for data workflows. Solid knowledge of containerization and orchestration: Docker and Kubernetes for deploying data services, batch jobs, and microservices in production. Strong grasp of data modeling: Dimensional modeling plus a clear understanding of trade-offs for operational vs analytical schemas. 💰 Salary: The expected salary range is around 75.000€ – 85.000 €, centered around the median. Final compensation will depend on experience and performance, with some flexibility within the range. What do we offer? See above for details.

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