Position: DevOps Engineer, Cloud Backend Services
Company: DataArt
Experience required: 2y
Category: DevOps
English level: intermediate
Published: 2022-02-01T00:00:00+02:00

ABOUT THE PROJECT
The client provides production solutions that include wearable devices and Cloud backend services. The product is designed to monitor the work environment to increase workplace safety. Devices send data to a server for real-time analysis. Alerts may help to prevent dangerous situations in the workplace. This is the first generation of the solution and now it has to cope with some architectural issues to increase scalability, reliability, and performance. At the moment our architects are working on analyzing it and preparing a plan for the implementation of the new version. The next phase is to build a new version. The team will consist of 8-11 specialists, the team size is to be clarified after the solution design phase. Technology stack and infrastructure: Java, Kotlin, Angular.io, MongoDB, PostgreSQL Within the project, you will: • Work with cloud service providers (mostly AWS but also Azure, GC and dedicated servers as well) • Work in a high load environment with a large amount of data using the Scrum methodology • Work on a long-term project.

Must have
Experience as a DevOps and/or SysOps engineer, architecting and deploying apps for both on-premise and cloud-based systems
Well versed with SRE practices
Experience with managing and deploying event-based architectures with Apache Kafka/ActiveMQ
Strong understanding and experience of Infra as code using Terraform, Ansible, Python, or cloud SDKs
Strong experience in capacity planning and deploying low latency, high availability, and fault-tolerant architectures.
Excellent knowledge of Security principles
Solid experience in building and deploying containarized apps
Experience with APMs and log aggregation pipelines in TBs
Experience with Various API gateways and serverless architectures.

Nice to have
Experience in building real-time low latency high volume data processing apps
Experience with Hybrid Infrastructure Management (on-premise and cloud-based)
Experience with Kubernetes, ArgoCD, and Kube Native Apps
Multicloud experience
Experience with deploying and scaling big data tech stacks
Experience with the IOT/IIOT domain. Knowledge of various IOT communication protocols and the required infrastructure for them
Experience with implementing GDPR, PCI-DSS, and other data privacy standards