Senior Data Engineer - Lounge by Zalando (all genders)

Role Senior Data Engineer for Lounge by Zalando. You will work alongside backend engineers and data scientists to build large‑scale recommender systems and design, build, and maintain machine‑learning pipelines at a global scale. Responsibilities - Design, build and optimise large‑scale ETL, streaming and batch processing pipelines. - Implement and maintain high‑throughput/low‑latency data stores for real‑time recommendations. - Improve data‑governance mechanisms to ensure data quality and reliability. - Build and enhance ML infrastructure, including training, evaluation and experimentation frameworks. - Collaborate with product managers, data scientists, engineers and analysts to create positive customer impact. - Contribute to architectural decisions and help define team objectives. - Support the self‑organisation of the team and adapt to multidisciplinary tasks as needed. Qualifications - Strong experience applying software‑engineering principles to data‑management systems; proficient in building robust, scalable data infrastructure using high‑quality code (beyond just SQL). - Minimum 3 years of data‑engineering experience. - Good understanding of distributed data‑processing mechanisms and ability to diagnose and optimise slow‑running pipelines. - Experience with large‑scale batch or stream processing (e.g., Spark, Hadoop, Flink, Storm, Apache Beam, Kafka). - Proficiency in Python or Java. - Strong understanding of distributed databases, especially high‑throughput/low‑latency stores such as DynamoDB, Cassandra or Redis (highly valued). What We Offer - Employee shares program. - 40 % discount on fashion and beauty products, 30 % off Zalando Lounge, plus external partner discounts. - Two paid volunteering days per year. - Hybrid working model with up to 60 % remote and up to 30 working days abroad per year. - 27 days of vacation starting, relocation assistance, family services, health and wellbeing options (Gympass), mental‑health support and coaching. - Continuous development through training platform and bi‑annual peer‑to‑peer review.