Cloud Architect

We are looking for a Cloud Architect to lead our cloud infrastructure team and own the reliability, scalability, security, and cost optimization of our CDP platform across all client environments. You will be a hands-on technical leader who sets the architectural direction for cloud infrastructure while managing a small, high-impact team. This is a leadership hire; you will report directly to the VP of Engineering and be accountable for infrastructure that processes billions of customer events monthly for enterprise clients in regulated industries.

Responsibilities:

• Define and own the cloud architecture strategy across AWS, GCP, and Azure.
• Manage and mentor a team of 2 DevOps engineers, growing the team as needed.
• Design and maintain infrastructure-as-code (Terraform, CloudFormation) for all environments: development, staging, production, and client-specific.
• Implement and manage CI/CD pipelines using GitLab CI/CD serving all engineering teams.
• Own the monitoring and observability stack, alerting, dashboards, incident response, and SLAs.
• Manage Kubernetes and container orchestration across all environments.
• Drive cloud cost optimization, targeting a 20%+ annual reduction through RI planning, spot instances, right-sizing, and architectural improvements.
• Ensure security compliance, access management, encryption, and audit trails for regulated industries.
• Design and maintain multi-tenant infrastructure for client isolation.
• Own disaster recovery, backup strategies, and business continuity planning.
• Own and operate Kafka clusters for broker management, topic configuration, consumer group monitoring, performance tuning, and scaling.
• Manage MongoDB infrastructure replica sets, sharding, backup, performance optimization, and capacity planning.
• Manage storage infrastructure across cloud object storage, block storage, database storage, lifecycle policies, and cost optimization.
• Collaborate with data platform teams on analytical database infrastructure (Snowflake, BigQuery) and integration with streaming pipelines.
• Support client-facing engineers with environment provisioning, scaling, and performance troubleshooting.
• Provision compute resources for data science model training.