Our systems are global-scale deployments of different services such as developer productivity tools, image and message processing systems, active and passive security scanning, big data and mapreduce clusters, messaging brokers, database and NoSQL backends and many more. We specifically have to support hundreds of services and hundreds of instances for our millions of consumers, using service discovery systems, autoscaling, dynamic load balancing and routing.

Scientists and engineers in our teams work to make hundreds of millions of user behaviour events from all around the world understandable for analysts and business users in the company, daily. This large data set is also one of the most diverse data sets in the world and we work with the latest data technologies (Spark, AWS services, Kafka). Tens of thousands of tasks are ran every day to handle data processing jobs at this scale.

For internal services (like delivery pipelines and build systems), we support more than a thousand developers and develop dozens of developer productivity utilities to have our developers code more with less hassle. At all times our engineers are just a git clone away from real code and our teams are active contributors to several public OSS projects.

Requirements:

• A BSc (or equivalent) degree in computer science
• AWS, Docker, Mesos, Kubernetes
• Kafka, Cassandra
• Strong UNIX background
• Python, Ruby, Go, Java, Perl
• Experience in building systems that scale
• Experience with modern deployment tools like Jenkins, Git, Puppet, Chef