ironquill.tech/board

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Python Developer

Lyst·UK·London, GB·mid
pythonjavascriptdjangoredispostgreselasticsearchdockerawsdata sciencemicroservicesios
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Lyst is a technology platform that revolutionises the way people shop for fashion. We connect millions of consumers globally with the world’s leading fashion designers and stores, giving them a simpler, more engaging and more effective shopping experience. Lyst has grown over 300% every year since launch in 2011 and has raised over $60M from top-tier investors including Accel, DFJ, Balderton and the teams behind LVMH, Michael Kors and Oscar de la Renta. We re looking for Software Engineers to take on challenges in the products that sit at the heart of Lyst. Our team is split into small vertical functions that handle everything from data ingestion, to our website to our universal checkout systems. You could be leading the design of a new system to rapidly detect external fashion trends, to solving challenges of international payments at scale, all the while helping us build a user friendly and commercially successful customer experience for one of the largest high-end fashion sites in the world. We re looking for several engineers to join us currently and this role will allow you to help Lyst build and grow products currently used by millions of users globally. You will work closely with our current engineers, data scientists, designers and product managers to develop new product features and help us execute our product strategy, with a stack comprised of Python, JavaScript, Django, PostgreSQL, Redis, AWS, iOS, Elasticsearch, Docker, Ember.js We re looking for experienced engineers that have managed to solve big challenges through ingenious ideas and execution. We would like to say we re language agnostic, but we re not really, with the majority of the codebase written in Python. We love Python. It s all Python, everything. Also Django. At the moment we re also really interested to speak to people who have solved large scale architectural challenges, built out services within a microservices environment and worked with Data Science teams. We like to speak to commerci

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