Full-Time Senior Platform (backend python) Engineer
NOTE: This job listing has expired and may no longer be relevant!
We are looking for an experienced product driven engineer. Our growing team is international and diverse, so we are welcoming everyone
Focus will be on handling large amount of data in multiple formats, not all normalized, work with services integration (REST, OAuth, analytics, payment) and finally with algorithms for graphs (social, content relationship, …), search and statistics.
Product-wise, you will be taking features from the idea stage to scalable production deployments. You will work on making highly scalable solutions, get feedback from analytics and monitoring tools and be able to refine and perfect your solution at each iteration.
Tech-wise, our server code is written in Python (Django) and you will be exposed to distributed computing (scalable stack, queue-driven distributed processing), cloud hosting (Amazon), database optimization (MySQL, Redis, MongoDB), search solutions (Sphinx, ElasticSearch), test driven development, load testing, etc.
In a senior position, you will work closely with our CTO, product designers and create a small team around you. You will be given new product areas to explore and build from architecture to deployment and feedback loop with the users. Our backend & ops team only have 5 members today, and we’re handling ~20m daily requests on dynamic app pages.
- You have worked on a large-scale consumer web/mobile applications.
- You have worked in a team of developers and know the benefits of tests, continuous integration, logging and monitoring
- You are interested by the trend of Quantified Self products (Fitbit, Moves, Withings, Wakemate, …)
- You have some (professional or personal) experience with Django, Python (and bonus for Amazon Web Services and distributed systems)
- You have or want experience in a fast growing startup
- You love building products and work for millions of users
- You like software design patterns, new data stores/engines and (bonus) the challenges of machine learning
How to Apply