Lyst

Python Developer

Lyst
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10 years ago
London, United KingdomSenior

Responsibilities

  • Design and develop new product features and systems used by millions of global users.
  • Solve large-scale technical challenges involving data ingestion, fashion trends, payments, checkout, recommendations, and customer experience.
  • Build services and contribute to architectural solutions using Python, Django, and the broader Lyst technology stack.
  • Collaborate with engineers, data scientists, designers, and product managers to execute product strategy.
  • Understand commercial objectives and help deliver a user-friendly customer experience.
  • Share technical knowledge and potentially mentor engineers or help build teams.

Requirements

  • Experience solving significant technical challenges through effective design and execution.
  • Strong Python and Django experience, given that most of the codebase is written in Python.
  • Experience addressing large-scale architectural challenges and building services in a distributed services environment.
  • Experience working with Data Science teams.
  • Commercial awareness and an understanding of business objectives and user experience.
  • Mentoring or team-building experience is valued.

Benefits

  • Twice-monthly internal engineering meetups.
  • Paid attendance at conferences and internal training opportunities.
  • Clothing allowance.
  • Desk beer Fridays and a stocked kitchen and fridge.
  • Regular office yoga, sports teams, board game nights, and burger clubs.
  • Opportunities to attend and speak at events such as PyCon, EuroPython, and PyData.

Tech Stack

Amazon RedshiftAWSDjangoDockerElasticsearchEmber.jsiOSJavaScriptPostgreSQLPythonRedis

Categories

Lyst

About Lyst

201-500 employees

Lyst builds a global fashion shopping and search platform that aggregates premium and luxury products from thousands of brands and retailers, earning revenue from referrals and checkout transactions. Founded in 2010 and headquartered in London, it was acquired by Zozo in 2025. The service lists over 8.5 million items from 17,000+ brands for roughly 200 million shoppers, and relies heavily on machine-learning search and recommendations.

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