Cloud Architect

We are seeking an experienced Cloud Architect to lead our cloud infrastructure team for the CDP platform. You will ensure reliability, scalability, security, and cost optimization across all client environments in regulated industries. Reporting directly to the VP of Engineering, this role involves setting architectural direction while managing a high-impact DevOps team.

• Define and own end-to-end cloud architecture strategy utilizing AWS, GCP, and Azure multi-cloud setups.
• Mentor and grow a team of 2+ DevOps engineers to maintain best-in-class operational standards.
• Implement Infrastructure-as-Code (IaC) using Terraform or CloudFormation for development, staging, production, and client-specific environments.
• Build and optimize CI/CD pipelines via GitLab CI/CD to support all engineering teams with seamless deployment flows.
• Establish robust monitoring, observability stacks, alerting systems, dashboards, incident response protocols, and SLA management.
• Spearhead Kubernetes operations for container orchestration across diverse environments.
• Drive cloud cost optimization initiatives targeting a 20%+ annual reduction through Reserved Instance (RI) planning, spot instance usage, right-sizing, and architectural efficiency improvements.
• Enforce strict security compliance, access management policies, encryption standards, and audit trails for regulated sector clients.
• Design secure multi-tenant infrastructure ensuring complete client data isolation.
• Led disaster recovery strategies, backup protocols, and business continuity planning to ensure high availability.
• Maintain Kafka clusters including broker management, topic configuration, consumer group monitoring, performance tuning, and scaling operations.
• Manage MongoDB replica sets, sharding architectures, backups, performance optimization, and capacity planning for data workloads.
• Orchestrate storage infrastructure across object, block, and database storage tiers with lifecycle policies focused on cost efficiency.
• Collaborate closely with data platform teams to design analytical databases (Snowflake, BigQuery) and integrate streaming pipelines effectively.
• Provide expert support for client-facing engineers regarding environment provisioning, scaling events, and performance troubleshooting.
• Provision scalable compute resources specifically optimized for training advanced machine learning models in Data Science workflows.