Parse.ly is a real-time content measurement layer for the entire web. Our analytics platform helps digital storytellers at some of the web's best sites, such as Arstechnica, The New Yorker, TechCrunch, The Intercept, Mashable, and many more. In total, our analytics system handles over 65 billion monthly events from over 1 billion 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. Our UX/design team has also built one of the best-looking dashboards on the planet, using AngularJS and D3.js. We are now expanding our reach into the area of petabyte-scale data analysis in order to deliver insights to our customers about how news and information flows online.
We’re the kind of team that does “whatever it takes” to get a project done.
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.
Working in concert with our Data Engineers and UX Engineers, as an Infrastructure Engineer you will take ownership of Parse.ly’s distributed cloud environment.
This environment involves 200+ servers running in 7 availability zones and 2 regions in Amazon Web Services.
We practice true DevOps -- infrastructure-as-code; reliance on automation/scripting; pervasive monitoring/alerting; and, careful distributed system design. In this role, you will code in Python, but be comfortable with scripting languages and orchestration tools. You will master AWS services, security practices, and APIs.
You will ensure that one of the most important real-time analytics systems in the world -- trusted daily by over 250 media companies, 2,000 website operators, and over 25,000 active dashboard user seats -- is leveraging the best high-availability and rapid-recovery techniques.
-
Own all code related to automated build-out of our cloud infrastructure. This includes code recipes that automatically build our EC2 boxes; monitoring/alerting scripts; cost reporting tools; and more.
-
Evaluate new technologies that assist Parse.ly’s data engineering and user experience teams at an infrastructure level. Examples of technologies evaluated in the past: Datadog APM, Varnish, Docker, Vagrant, AWS Elasticache, AWS RDS, Logstash/Kibana, PgBouncer.
-
Assist in the roll-out of critical services. For example, one of our Infrastructure Engineers recently assisted with the roll-out of a new Python Tornado based API server, replacing a service that’s hit by our customers more than 2 billion times per month. This upgrade happened with no customer service interruptions and no server downtime.
-
Gain operational expertise for core data infrastructure technologies, including Amazon S3, Kafka, Zookeeper, Storm, Cassandra, Elasticsearch, Redis, Postgres, and Spark.
-
Report on improvement of key Service-Level Objectives (SLOs) within Parse.ly, such as API response times, service uptime, end-to-end data processing latency, and more.
-
Past experience programming in Python
-
Depth of experience with AWS
-
Deep love of UNIX/Linux
-
Comfort with shell scripting and server automation
-
Has read all or part of “Site Reliability Engineering” book from Google/O’Reilly (available free here)
Parse.ly is a fully distributed team, with engineers working from across the world. People with past experience working remotely will be prioritized. US/Eastern timezones will be prioritized.
Send a cover letter, CV/resume, and optionally links to projects or code, to the email address here: work@parsely.com. Make sure to indicate you are applying for the "Infrastructure Engineer" role.