The Role 

We’re looking for an experienced engineer to join our highly skilled team and build the back-end of our award-winning MSX® data analytics platform. The role will provide the opportunity to work directly with our customers – traders, salespeople and technologists at leading investment banks.

The ideal candidate is a hands-on engineer who cares passionately about the quality of their work and the satisfaction of the end user. We are looking for someone who can work well within a team, is able to articulate problems, and can use their own initiative to identify and implement solutions. This role is part of a broader recruitment effort to scale the organization to meet market opportunity. This role offers a unique opportunity to join a successful start-up and to share in our future growth as we embark on the next step of our incredible, industry-enabling journey.

Key Responsibilities

•  Define and implement the DevOps strategy for a real-time data analytics platform which leverages many open source technologies
•  Define and implement our on-premise and cloud-hosted model, including deployment, support and security


Skills and Experience 


•  Experience with CI/CD, configuration management and orchestration tools (Ansible, Puppet, Jenkins, Terraform, IaC). Currently: Ansible, Jenkins, Docker
•  Experience with deploying, managing, troubleshooting and supporting complex distributed systems in production environment. Our stack: Kafka, Spark, HDFS 
•  Experience with monitoring, automation, alerting, deploying distributed systems, virtualization, configuration management, continuous integration, database administration
•  Understanding of networking, security and cloud based infrastructure
•  Strong Bash scripting skills
•  Hands on experience with Jenkins, Docker
•  Comprehension of application architecture


•  Previously developed custom Ansible plugins
•  Strong knowledge of any high-level programming languages
•  Experience deploying and managing Ignite, Druid
•  Experience with ELK stack etc.
•  Experience working with big data sets (preferably financial data)

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