Backend Engineer - Product Data Quality (hybrid)

at  Zalando

ABOUT THE ROLE :

The Product Data Quality team is looking for a talented Software Engineer who has a passion for building applications at the intersection of data science, data engineering and software development. Our team consists of a great mix of Software Engineers, Product Managers and Applied Scientists that are tasked with gaining insights into our assortment of hundreds of thousands of live products using AI, and then bringing these insights to our customers at scale in new and engaging ways.
As a member of the Product Data Quality team, you will spearhead the design, development, deployment, and monitoring of cloud-based microservice architectures. You will work closely with Applied Scientists and Product Managers to deploy and manage state-of-the-art machine learning models for text and image analysis, enriching our product information in both synchronous and asynchronous workstreams in a scalable and sustainable manner. Additionally, you’ll enable new methods for customers to seamlessly navigate and gain profound insights into our product assortment on the Product Details Page. Our cutting-edge technology stack encompasses Python, Kotlin, AWS, Databricks, Kubernetes, RESTful APIs, Tensorflow, PyTorch, Elastic Search, and Postgres amongst others. Check our Engineering Blog for more information about us!

WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)

• Design, development and deployment of the team’s systems, demonstrating seasoned expertise.
• Design, construct, and maintain resilient software architectures adaptable to evolving product requirements.
• Consistently deliver high-quality, testable, and dependable systems, fostering a culture of excellence through comprehensive reviews and mentorship.
• Embrace agility by iteratively testing features with stakeholders while maintaining a holistic perspective on project goals.
• Exhibit robust stakeholder management skills, fostering effective communication and collaboration with engineering peers, applied scientists, and product owners throughout the organisation.
• Prioritise team processes, automation, communication, and collaboration to bolster the team’s velocity and output, driving toward collective success.