Kubernetes Infrastructure Engineer (India)
Team: Engineering
Location: Bangalore
Commitment: Fulltime
Workplace Type: hybrid
The Impact You Will Drive:
- As a Kubernetes Infrastructure Engineer at Onehouse, you will build a world class software development and deployment on Kubernetes infrastructure of a product on that is revolutionising the big data processing and AI workloads across multiple clouds, all at once.
A Typical Day:
- Be the go to person for all things Infra.
- Collaborating with your stakeholders in data platform, backend and frontend to achieve key deliverables
- Implement infrastructure-as-code for multiple environments
- Iterate on best practices to increase the product quality & velocity of deployments
- Work on improving automation for monitoring and oncall processes
- Support and work alongside a cross-functional engineering team on the latest technologies like Spark, Kubernetes, Prometheus, Kafka, Debezium etc.
- Manage security and access control for entire organization (IAM/SSO management)
- Uphold a high engineering bar around the code, monitoring, operations, automated testing, release management of the platform
- Handling of production alerts, incidents and writing good well-organized on-call runbooks, documentation and post-mortem reports
What You Bring to the Table:
- 5+ years of experience as a platform engineer with operational excellence in monitoring/deploying/testing microservice architectures.
- Experience with managing Kubernetes clusters and applications
- Experience deploying applications on one or more cloud platforms (AWS/GCP/Azure).
- Experience with infrastructure-as-code (e.g. Terraform, Cloudformation)
- Experience with automation frameworks (e.g. Jenkins, CircleCI)
- Experience with monitoring stacks (e.g. Prometheus and ELK)
- Experience with cloud security management (e.g. IAM, SSO)
- Great problem-solving skills, a keen eye for details
- Quick decision making, self-driven and able to balance to feature development and tech debt
- Clear communication skills
- Nice to haves (but not required):
- Experience with data processing technologies like Spark
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