Bloomberg is a premiere provider of data. We combine news and data from more than 80,000 new wires, 4,000 FX feeds and 370 exchanges around the world totaling more than 60 billion ticks a day.
Our technology allows our customers to exchange more than 300 million messages and nearly 17 million chats daily.
We build real-time software for high impact systems that is core to the Bloomberg infrastructure. We process market data from around the world, driving the majority of downstream Bloomberg applications.
We address the market demand for low-latency solutions by delivering the world's most reliable, timely and accurate financial data.
What’s your role in this?
As a System Reliability Engineer - Real Time Distribution Platform at Bloomberg, your mission is to drive the automation of our production operations, everything from reaction to failures, deployment, testing, and quality checks.
You will ensure the optimal availability, latency, scalability, and efficiency of more than ten thousand client-facing applications.
We’ll expect you to own our production environment from the initial design phases to ensuring continuous high availability.
You should be comfortable working alongside other engineers to help fix and debug issues with the production environment.
We’ll trust you to :
Investigate, triage, and troubleshoot production problems as they occur
Build and maintain common and integrated standards with respect to logging, latency, troubleshooting, and monitoring
Develop and maintain tools used in investigating production problems
Develop and maintain services to effectively manage configurations across thousands of machines
Review and influence the design and standards of the software
Measure current capacity, predict future capacity needs and make suggestions accordingly
Automate deployment and configuration management, quality (including functional and capacity testing), and reaction to problems-
Facilitate continuous integration / continuous deployment
You’ll need to have :
Proven understanding of how large-scale production systems are put together and experience with triaging and solving problems with them
Hands-on experience in C / C++, Python or any other programming language
Strong knowledge of Linux systems
We’d love to see :
Familiarity with configuration management tools such as Chef, Puppet, Ansible or Saltstack
Practical knowledge of networking such as TCP / UDP / IP
Familiarity with monitoring tools; Splunk, ELK, Grafana, Nagios.
Experience with virtualization technologies Vagrant, Terraform, VMWare or KVM
Knowledge of cloud technologies (OpenStack, AWS, Rackspace, CloudFoundry, OpenShift, WS02)
Knowledge of containerization technologies such as Docker, Mesos, Core OS, Kubernetes