Senior Data Engineer Lounge by Zalando (all genders)
Job Summary
Lounge by Zalando is a rapidly growing part of Zalando now turning over billions of euros each year. That said there is so much untapped potential with respect to personalization and recommendation.
You will be a data engineer working alongside backend engineers and data scientists to build large-scale recommender systems. As the largest online fashion retailer in Europe we require a skilled engineer who can design build and maintain Machine Learning pipelines at a global scale.
You will play a key role across the entire ML lifecycle from designing and implementing robust batch and streaming preprocessing pipelines to enabling efficient model training and distribution for our real-time recommender systems. This is a very good opportunity to build a data product that has a measurable impact on the business outcomes and the user experience. You will have significant input into architectural decisions and help to implement state of the art ML recommender algorithms. There are very few roles that offer this unique synthesis of scale and ML complexity.
Our team thrives on a multidisciplinary approach and while this role is primarily focused on data engineering development we highly value individuals who are adaptable and willing to contribute to other areas as needed fostering a truly collaborative environment.
At Zalando our vision is to be inclusive by design. And this vision starts with our hiring - we do not discriminate on the basis of gender identity sexual orientation personal expression ethnicity religious belief or disability status. You are welcome to leave out your picture age or marital status from your application. We only assess candidates on their qualifications and merit.
We want to provide you with a great candidate experience. Feel free to inform us of any accommodations you may need so we can best support you throughout the hiring - our diversity & inclusion strategy: employee resource groups: WED LOVE YOU TO DO (AND LOVE DOING) Design build and optimize large-scale ETL stream and batch processing pipelines. Implement and maintain high-throughput/low-latency data stores (e.g. for real-time recommendations). Implement and improve data governance mechanisms to ensure data quality and reliability. Accelerate the pace of innovation by building and improving ML infrastructure such as training and evaluation frameworks experimentation frameworks. Collaborate with brilliant Product Managers Data Scientists Engineers and Analysts across Zalando to create positive customer impact together. Help define our teams objectives. Continuously improve the self-organization of the team. Strong experience applying software engineering principles to data management systems. You should be proficient in building robust scalable data infrastructure using high-quality code not just SQL. 3 years of experience in data engineering projects. Good understanding of distributed data processing mechanisms. You should be able to diagnose and optimize a slow-running data pipeline. Experience with large-scale batch processing and/or stream processing (e.g. Spark Hadoop Flink Storm Apache Beam Kafka.) Proficient in either Python or Java. A strong understanding of distributed databases especially high-throughput/low-latency data stores (e.g. DynamoDB Cassandra or Redis) is highly valued. OUR OFFER Zalando provides a range of benefits heres an overview of what you can expect. Ask your Talent Acquisition Partner to learn more about what we offer. Employee shares program 40% off fashion and beauty products sold and shipped by Zalando 30% off Zalando Lounge discounts from external partners 2 paid volunteering days a year Hybrid working model with up to 60% remote per week Work from abroad for up to 30 working days a year 27 days of vacation a year to start Relocation assistance available (subject to prior agreement) Family services including counseling and support Health and wellbeing options (including Gympass) Mental health support and coaching available Drive your development through our training platform and biannual peer-to-peer review
Required Experience:
Senior IC