Vacancy caducado!
- Perform Big Data cluster capacity planning
- Perform benchmarking on various Big data tools and technologies and articulate pros and cons
- Implement end to end Big Data cluster security thru Role based access control
- Implement batch orchestration using AirFlow
- Create application containers and orchestrate them using OpenShift/Kubernetes
- To be able to architect Big Data, AI/ML solution in Cloud preferably Microsoft Azure
- Proficient and hands-on cloud native PaaS such as SQLDW, Stream Analytics, Appinsight and Azure Databricks
- Develops SHELL, PERL and PYTHON scripts to accomplish day to day system administration tasks and to support business application requirements
- Minimum 5 years as an Infrastructure DevOps or automation engineer
- Proficient in server side scripting
- Knowledge of DevOps capabilities such as Continuous Integration and Delivery (CI/CD), Automated Testing, etc.
- Knowledge on Terraform is must preferably in Azure
- Good exposure on Microservices architecture and their deployment in cloud world. (Especially Azure +Terraform)
- Should have worked on setting up & troubleshooting Kubernetes Clusters in Production ready environment
- Help teams in migration from monolithic application to Microservices using containerization solutions (Docker, Kubernetes)
- Worked on onboarding Microservices (Middleware/UI) components using DevOps technique & look for improvements
- Prior experience in automating CI/CD process, platform services using open source tools
- Azure or AWS certification is preferred
- Knowledge of Databricks and Azure AppInsight is a big plus
- Knowledge of No-SQL databases and Big Data (MongoDB, Casandra etc.)
- Knowledge of JIRA system to log problems, bug fixes for Development book of work.
- Experience on Splunk tool or any Log Management tool
- Experience in Snowflake.
Vacancy caducado!