Platform / Devops Engineer

What You Will Do

• Cloud infrastructure architecture and operations (Azure and AWS)
• Container orchestration at scale (Kubernetes)
• Data platform infrastructure (Spark/Databricks)
• Platform observability, performance optimization, and cost management
• Infrastructure automation and self-service capabilities
• Incident response and system resilience

Major Initiatives You'll Drive

• Observability: Build comprehensive monitoring, logging, and tracing systems that provide actionable insights into platform health and performance.
• Production Scalability & Reliability: Ensure our platform scales efficiently to meet customer demand while maintaining high availability and performance.
• Optimization: Drive FinOps practices and cost-aware architecture decisions across our Cloud infrastructure.

Responsibilities

• Cloud infrastructure architecture and operations (Azure and AWS)
• Container orchestration at scale (Kubernetes)
• Data platform infrastructure (Spark/Databricks)
• Platform observability, performance optimization, and cost management
• Infrastructure automation and self-service capabilities
• Incident response and system resilience

Qualifications

• 4-6+ years working with production systems at scale
• Hands-on experience with cloud infrastructure (Azure or AWS preferred)
• Programming ability (Python, Rust, Go, Bash, or others)
• Understanding of distributed systems, reliability, and observability
• Experience with infrastructure automation and configuration management
• Demonstrated ability to work effectively in remote environments

Required Skills

• Experience operating Kubernetes in production environments
• Familiarity with data platform infrastructure (Spark, Databricks, or similar)
• Multi-cloud experience (Azure and AWS)
• Hands-on experience with observability tools and practices
• Track record of improving system reliability and scalability
• Experience with cloud cost optimization and FinOps practices
• Infrastructure as Code tools (Terraform, Pulumi, or similar)

Preferred Skills

• Leadership experience or potential
• ML/AI infrastructure experience
• Security and compliance knowledge
• Incident management and on-call practices
• Performance tuning and capacity planning