Senior Python Developer - Microservices

The main challenge now is to build a scalable architecture, meaning we have to tackle the challenges that come with using Python for distributed systems; Consistency, availability, service orchestration and much more.

We currently run different services, all with their own CI flows, allowing us to deploy several times a day.

In this role you will join a small, lean team of software engineers and a product manager working on;

• Building the integrated payment and checkout system using Python as well as the latest tools, technologies and methodologies.
• Supporting partner integration teams and ensuring that integration with partner retail checkout systems and API’s is easy and effortless
• Integrations with 3rd party payment systems such as (Stripe, Klarna, Apple Pay etc)
• A secure data management and CRM system for internal and external stakeholders (owasps etc)
• New ways to automate onboarding for retailers that allows for global regulations.

HOW WE WORK

• We are developing an environment and culture that is all about writing great software using the best tools in the best possible manner.
• We like to build things that solve problems, you will not be constrained by process - we work in small product teams that take a lean approach to building things.
• In this team we’re looking for engineers who are excited to work on secure technologies in a python environment. You will ideally have plenty of experience using;

• Python, postgresql, jenkins, circleci, aws, redshift, redis, django, rest framework...
• Docker (http://developers.lyst.com/devops/2014/12/08/docker)
• Microservices architecture (HTTP)
• TDD - We love tests!
• We are using both Kanban and Scrum, depending if team is more customer facing or internal (Jira)

You will be challenged, supported and have the opportunity to learn a lot. You will work a fast paced, autonomous environment with like minded people who are passionate about what they do:

• 50 engineers and data scientists
• 5M duplicated products detected and merged using product image features (http://www.slideshare.net/ejlbell/fashion-productdeduplication)
• 300k online recommendation model updates per day (http://developers.lyst.com/data/2014/11/11/word-embeddings-for-fashion/)
• 72k crowd-sourced labels generated per day
• 40k product gender classifications per day via deep learning
• 500k recommended products per day
• 120 EC2, 8 RDS, 7 ElastiCache and 10 Redshift instances
• our internal analytics system collects ~100M data points/day

...and a team that…

• ~10 deployments/day
• 40+ merged pull requests/day
• 20k lines of change/week
• Lots of open source projects - https://github.com/lyst and https://github.com/SSAW
• Get invited to talk at great events (PyCon, Europython, PyData etc)
• feature toggling and A/B testing