Parse.ly has built a real-time content measurement layer for the entire web.
Parse.ly's analytics platform helps digital storytellers at some of the web's best sites, such as Arstechnica, New Yorker, The Atlantic, The Next Web, and many more.
In total, our analytics backend system needs to handle over 40 billion monthly events from over 550 million monthly unique visitors.
Our entire stack is in Python and JavaScript, and our team has innovated in areas related to real-time analytics, building some of the best open source tools for working with modern stream processing technologies. These include pykafka, pystorm, and streamparse.
Our UX/design team has also built one of the best-looking dashboards on the planet, using AngularJS and d3.js. You can see some screenshots at http://parse.ly/tour.
Our distributed team is best-in-class and we happily skip commutes by working out of our ergonomic home offices.
Here's a photograph of mine running two full-screen Parse.ly dashboards on my monitors: https://flic.kr/p/v1NZ73
We are currently looking for front-end engineers to help us build the best real-time analytics dashboard the world has ever seen. The requirements: programming background in Python and JavaScript, emphasis on JavaScript. Bonus points for an interest in information visualization and Edward Tufte. You can't be a frontend web coder only -- you need to be willing to be a flexible Python programmer, too.
This role will involve you rolling up your sleeves to debug queries generated by our Python data access layer or optimize middle-tier performance through caching with Redis. But it'll also have you applying advanced in-browser dataviz and UX techniques with d3.js and AngularJS, and thinking through the way to best satisfy customer demands around real-time content analytics data.
We are also hiring backend engineers to expand our data platform and make the world's most flexible and highest-performance real-time content analytics system. On this team, you'd be working with Python experts in using Storm, Kafka, Cassandra, Elasticsearch and Redis at scale.
Finally, we have an opening for a Python engineer particularly interested in automated testing of API servers, third-party JavaScript, and rich web/mobile applications via modern frameworks like Locust, WebDriver, PhantomJS, and Appium.
Apply to any of these roles now by sending a CV/website, github/dribbble links (if available), and 1 paragraph intro to work@parsely.com. Let us know what part of the position interests you. Also, mention the HN Who's Hiring thread.
Parse.ly has built a real-time content measurement layer for the entire web.
Parse.ly's analytics platform helps digital storytellers at some of the web's best sites, such as Arstechnica, New Yorker, The Atlantic, The Next Web, and many more. In total, our analytics backend system needs to handle over 40 billion monthly events from over 550 million monthly unique visitors.
Our entire stack is in Python and JavaScript, and our team has innovated in areas related to real-time analytics, building some of the best open source tools for working with modern stream processing technologies. These include pykafka, pystorm, and streamparse.
Our UX/design team has also built one of the best-looking dashboards on the planet, using AngularJS and d3.js. You can see some screenshots at http://parse.ly/tour.
Our distributed team is best-in-class and we happily skip commutes by working out of our ergonomic home offices.
Here's a photograph of mine running two full-screen Parse.ly dashboards on my monitors: https://flic.kr/p/v1NZ73
We are currently looking for front-end engineers to help us build the best real-time analytics dashboard the world has ever seen. The requirements: programming background in Python and JavaScript, emphasis on JavaScript. Bonus points for an interest in information visualization and Edward Tufte. You can't be a frontend web coder only -- you need to be willing to be a flexible Python programmer, too.
This role will involve you rolling up your sleeves to debug queries generated by our Python data access layer or optimize middle-tier performance through caching with Redis. But it'll also have you applying advanced in-browser dataviz and UX techniques with d3.js and AngularJS, and thinking through the way to best satisfy customer demands around real-time content analytics data.
We are also hiring backend engineers to expand our data platform and make the world's most flexible and highest-performance real-time content analytics system. On this team, you'd be working with Python experts in using Storm, Kafka, Cassandra, Elasticsearch and Redis at scale.
Finally, we have an opening for a Python engineer particularly interested in automated testing of API servers, third-party JavaScript, and rich web/mobile applications via modern frameworks like Locust, WebDriver, PhantomJS, and Appium.
Apply to any of these roles now by sending a CV/website, github/dribbble links (if available), and 1 paragraph intro to work@parsely.com. Let us know what part of the position interests you. Also, mention the HN Who's Hiring thread.
p.s. to see an example of how we work, check out the blog post, "Whatever It Takes": http://blog.parsely.com/post/46