Principal Data Engineer - Ranking & Visibility (all genders)

Role: Principal Data Engineer - Ranking & Visibility As a Principal Data Engineer in our team, you will serve as the data architecture, data modeling, and engineering backbone that powers our analytics, statistical modeling, and data-driven products. You will transform complex, high-volume upstream datasets, including event tracking, into clean data layers utilized directly by Applied Scientists and Analysts. Your work will bridge the gap between raw data streams and production execution, translating complex upstream event signals into high-impact modeling inputs. Unlike a traditional data engineering role focused solely on infrastructure, this position carries an equally important mandate in data modeling and collaborative model productionization. You will work side-by-side with Applied Scientists to operationalize prototype models, ranging from classical statistical frameworks to machine learning, ensuring critical structural and architectural data choices are made to run them reliably at scale. You will collaborate closely with Applied Scientists, Analysts, Data Engineers, Product Managers, and upstream engineering stakeholders across the organization. Responsibilities: - Identify relevant tracking events across complex streams, making intentional data modeling choices to build high-quality, standardized, and well-documented data products for downstream scientists and analysts. - Partner directly with Applied Scientists to transform model prototypes (statistical or ML) into robust, maintainable, and low-latency production pipelines. - Lead data modeling strategy across production datasets and model pipelines, making critical structural and schema decisions to ensure long-term performance, correctness, and maintainability. - Design, build, and optimize pipelines, establishing rigorous standards for data quality, testability, monitoring, and pipeline health. - Set engineering standards, mentor team members, and drive large-scale data architecture initiatives across multidisciplinary teams. Qualifications: - Bachelor’s, Master’s, or equivalent practical experience in Computer Science, Data Engineering, Software Engineering, or a related quantitative field with 6+ years of relevant industry experience. - Led the design of pipelines or data platforms that several teams use, with measurable gains in reliability or cost. - Proven experience operationalizing prototype models developed by Applied Scientists into production execution environments. - Strong Pyspark, Python and SQL skills, including maintainable code, software design principles, unit testing, debugging, and code reviews. - Proven experience building and operating data pipelines, covering batch processing and real-time or streaming workloads, using technologies such as Apache Airflow, Apache Spark, and Apache Flink or equivalent frameworks. - Strong understanding of databases, data modeling, distributed processing, and query and storage performance optimization. - Experience operating production data pipelines, including monitoring, alerting, incident management, root cause analysis, and reliability and cost optimization. Hands-on CI/CD and cloud infrastructure, ideally AWS. - Experience with statistical data modeling. What We Offer: - 27 days of holiday a year to start for full-time employees (+1 day for every calendar year up to 30 days) - 40% off fashion and beauty products sold and shipped by Zalando, 30% off Lounge by Zalando, discounts from external partners - Family support, including counselling and dedicated services for parents and carers - Company pension scheme - Employee shares programme - Health and wellbeing options, including Wellhub - Mental health support and coaching - Development through our training platform and biannual peer-to-peer review - 2 paid volunteering days a year - Relocation assistance (subject to prior agreement)