Jobs at Zalando

As a Principal Software Engineer, you'll lead multiple teams in Risk Management, designing cloud-based solutions, mentoring engineers, and driving innovation.

Build and operate a centralized Data Lakehouse: design and maintain end-to-end ELT/CDC pipelines with Databricks DLT, ensure data quality and governance via Unity Catalog, collaborate across teams, translate business needs into performant Lakehouse data products (Gold layer), and document best practices.

The Senior Principal Software Engineer will lead logistics software development, enhancing automation, and AI integration, while managing complex projects and mentoring teams.

Lead design and implementation of high-performance Java/Spring Boot microservices and REST APIs. Own full lifecycle from Gradle builds to AWS/Kubernetes deployments, CI/CD, testing, and observability. Ensure resilient, secure, cost-efficient systems, mentor engineers, collaborate across product and frontend teams, and drive technical standards.

Provide expert SAP BRIM (FI-CA-INV/FI-CA) support for O2C B2B/B2C processes across S/4HANA landscapes. Resolve complex incidents, drive process improvements, mentor a subteam, manage stakeholders, maintain documentation, and deliver training while promoting automation and Clean Core principles.

Lead product vision and roadmap for post-purchase experiences (order, support, returns) across apps and web. Drive data-informed, AI-enabled feature development, cross-functional discovery and delivery, KPI-driven experimentation, mentorship, and platform-level productization to increase engagement and repeat purchases for millions of customers.

Own the vision, strategy, roadmap, and commercial outcomes for Zalando’s Campaign & Content Platform. Lead cross-functional alignment across product, engineering, and design; use analytics, experimentation, customer research, and AI to improve publisher workflows and customer engagement. Navigate executive stakeholders, drive complex launches, mentor product managers, and establish scalable mechanisms for decision-making, ROI measurement, and content innovation.

Provide SRE support across monitoring, alerting, incident management (L3), root-cause analysis, performance and load testing, security vulnerability scanning, compliance (ISO27001/SOC2/GDPR), and automation to ensure stability, scalability and observability of cloud-native applications.

Lead a cross-functional team to implement AI-driven automation and self-service for customer enablement. Define and execute the product and AI roadmap, govern a single source of knowledge, map customer journeys, enable predictive performance and root-cause transparency, and upskill the team to shift from reactive operations to automation-first, scalable service delivery.

Manage end-to-end purchase-to-pay operations, including purchase order entry, delivery scheduling, product master data, supplier communication, contractual support, product availability, and returns coordination. Maintain accurate order and supplier information in merchandise systems, collaborate with internal and external stakeholders, and identify process improvements across pre-season and in-season operations.

Lead and grow cross-functional engineering teams in Helsinki, set technical roadmaps, ensure scalable cloud-native systems, drive AI/ML adoption, ensure reliable production operations, engage stakeholders, and foster engineering culture and delivery excellence.

Leads the creation of Tradebyte’s Product Marketing function and platform-led growth strategy. Owns positioning, messaging, end-to-end go-to-market architecture, market intelligence, product roadmap feedback, launch processes, and cross-functional alignment across Product, Sales, Customer Success, and Marketing. Builds the team, operating model, frameworks, and playbooks from scratch while driving commercial impact in a B2B SaaS fashion-tech environment.

Lead the design, development, deployment, and monitoring of scalable data pipelines, dashboards, and cloud-based architectures. Build systems that combine machine-learning insights from multiple data sources to improve product information. Collaborate with data, software, applied science, and product teams; maintain resilient microservices and data platforms; ensure high-quality, testable systems through reviews, automation, documentation, and mentorship.

Design, build, and optimize large-scale batch and streaming ETL pipelines and ML infrastructure for real-time recommender systems. Implement high-throughput/low-latency data stores, ensure data governance and quality, collaborate with product, data science, and engineering teams, and influence architecture and team objectives to deliver measurable business impact.

Develop production-grade machine learning models for large-scale demand forecasting and algorithmic pricing. Apply deep learning, gradient-boosted trees, causal inference, and operations research to optimize profit and inventory risk. Conduct data analysis, formulate scientific hypotheses, deploy and monitor models using Databricks, and collaborate with data scientists, software engineers, and product managers.

The Senior CRM Process Owner will optimize partner experiences by improving workflows and driving AI-enabled efficiency within the Salesforce ecosystem. Responsibilities include process design, stakeholder management, and training end-users to ensure high adoption rates and quality assurance.

As a Senior Applied Scientist, you'll develop advanced modeling techniques for marketing effectiveness, optimize marketing investments, and mentor junior scientists.

Lead end-to-end strategic initiatives to design, scale and govern creator programs. Build operating models, SOPs and tooling, run engagement experiments, analyse performance, and drive cross-functional alignment to optimise creator content and processes.

Provide high-level administrative and organizational support to the SVP Markets and leadership team. Manage schedules, priorities, meetings, travel, expenses, communications, onboarding, events, offsites, workshops, and cross-functional initiatives. Act as a gatekeeper, coordinate stakeholders, maintain administrative processes, and handle confidential information with discretion. Partner closely with the Chief of Staff, Executive Project Manager, MB Office team, and broader leadership organization.

Analyze and transform recommerce data into actionable insights supporting Pre-owned and Trade-in growth. Build and improve data landscapes, automate reports and dashboards, communicate findings to stakeholders, and support strategic commercial decisions. Collaborate with Data Engineering, Business Development, Product, Operations, and management teams to scale Zalando’s second-hand services.