Lead Backend Engineer - Personalization (all genders)

Description

The role is open to all genders and sits in the Personalization area, where the Search, Recommendations and Sorting teams work together to build a relevant, personalized shopping experience for millions of the company's customers.

The teams belong to the Customer & Shop Intelligence cluster.

Depending on your background, you could lead technical work in Search and how customers find products, in Recommendations and personalized product and outfit experiences, or in Sorting, where ranking systems balance relevance, ML and business rules.

You would own technical decisions beyond your own team, help shape architecture and engineering standards, and work with engineers, data scientists, analysts and product managers on scalable systems that matter to customers and the business.

The company is one of Europe's fastest-growing e-commerce businesses and works at the crossover of fashion and technology. It keeps hierarchies flat, communicates directly and makes pragmatic decisions without long approval chains.

Responsibilities

• Take technical ownership of complex backend systems in Search, Recommendations or Sorting, from concept through to production.
• Design high-throughput, low-latency services and help develop the technical foundations of the Personalization area.
• Build and run systems that combine ML models, search and ranking algorithms, behavioral signals and business logic.
• Make technical decisions across team boundaries and set standards that make systems more scalable, reliable and maintainable.
• Partner with data scientists, data engineers, analysts and product managers to turn data and experiments into product improvements.
• Coach and support other engineers, share your expertise and raise the technical bar across the teams.
• Explore new technologies and approaches, propose your own ideas and help improve how systems are built and operated.

Requirements

• You have 7+ years of experience building scalable backend systems and APIs, and a clear record of owning technical work.
• You have recent, hands-on work in a typed language such as Node.js/TypeScript, or deep experience with Java, Go or Kotlin.
• You understand backend architecture, distributed systems, APIs, data stores and performance optimization well.
• You think algorithmically and analytically, and you are drawn to search, recommendations, ranking or personalization problems.
• You have worked where backend engineering meets ML, for example by serving model scores, embeddings or ML-driven features in production.
• You care about code quality and maintainability, and you push technical improvements beyond your immediate area.
• You are comfortable making architecture decisions, questioning existing approaches and setting engineering standards across teams.
• You communicate well in English and collaborate effectively with engineers, data experts and product stakeholders.
• You like taking ownership, sharing knowledge and helping other engineers grow.
• You have a solid technical background in Search, Recommender Systems, Ranking or Personalization.
• You have hands-on experience with Elasticsearch/OpenSearch, Redis/Valkey, high-throughput APIs or other performance-critical backend systems.
• You are familiar with ML-powered systems, LLMs, embeddings, vector search or Learning-to-Rank approaches.
• You have operated large-scale systems with strict latency and availability requirements.
• You have exposure to cloud platforms such as AWS or GCP and data platforms including BigQuery, dbt or Dagster.
• You come from e-commerce, search, recommendations, advertising or another field where relevance and personalization directly shape the customer experience.

Conditions

The company is based in Hamburg and Berlin.

The company aims for an environment where everyone feels welcome as they are, and it values diverse backgrounds and perspectives.

Benefits

• The company lists its perks on a dedicated benefits page.
• The team shares team lunches, afterwork drinks, company events and quick coffees between meetings.