Staff Engineer - Data Platform (m|w|d)

Job description

Reliable pipelines, resilient infrastructure and a scalable data platform are the foundation of every data-driven decision at idealo. As we accelerate toward real-time analytics, personalization and data monetization, the Data Platform is the engine that makes it possible. As a Staff Engineer, you’ll shape the technical foundation of the platform that thousands of daily data workloads depend on—and drive the strategic initiatives that will define what it can do next. This role combines platform engineering, cloud architecture and data engineering. You’ll influence how workloads are orchestrated across the platform, how infrastructure scales with demand and how technical decisions support idealo’s long-term data strategy. You’ll work in a modern engineering environment where state-of-the-art AI tooling—such as Claude Code—is available to accelerate your day-to-day work. About your new role Architect and develop cloud-native platform components, infrastructure automation and pipeline frameworks, with a strong focus on performance, security and maintainability. Lead technical initiatives within and across the team to align platform capabilities with business and product needs. Identify technical risks early and keep architecture decisions and technical concepts traceable across project phases. Drive continuous improvements across CI/CD pipelines, infrastructure as code, observability and monitoring. Structure technology choices as clear trade-offs—evaluating performance, cost, maintainability and integration—to inform strategic decisions. You’ll play a key role in shaping two of idealo’s most strategic platform initiatives: Personalization and Data-as-a-Service (DaaS). For Personalization, you’ll define and build a next-generation, privacy-first platform from the ground up, establishing the technical vision, architecture and engineering standards that enable highly relevant experiences across the entire customer journey for millions of users. In parallel, you’ll drive the evolution of our DaaS platform by researching, prototyping and validating new capabilities around real-time data processing, streaming technologies such as Kafka and Kinesis, and ML/AI integration. You’ll build scalable data products that enable data monetization and create new business opportunities. Working across Data Engineering, Software Engineering, Cloud, Platform, Product and Machine…