Design microservices architecture on AWS (ECS/Fargate, API Gateway, Lambda, etc.) with event-driven patterns (EventBridge, SNS/SQS)
Architect data platform: Snowflake warehouse, S3 Data Lake (Iceberg), real-time CDC pipelines, ETL/ELTpipelines, RBAC/ABAC security model
Define ML platform architecture: SageMaker pipelines, Feature Store, Model Registry, Bedrock integration for Gen AI
Lead integration strategy for enterprise systems (Hexagon, Salesforce, JD Edwards) via APIs, CDC, and ETL patterns

8+ years of software engineering experience, including 4+ years in architecture-focused roles
AWS Solutions Architect certification (Professional level preferred)
Proven experience working with enterprise-scale distributed systems
Must-have Technologies & Skills
AWS Architecture: Hands-on experience with VPC, ECS/Fargate, API Gateway, Lambda, Step Functions, EventBridge, SNS/SQS, ALB, and CloudFront
Data Architecture: Strong knowledge of Snowflake (architecture, RBAC/ABAC, performance optimization), S3 Data Lake, Apache Iceberg, and CDC patterns (DMS, Debezium)
Security & Compliance: Experience with IAM, Enterprise SSO, KMS, Secrets Manager, WAF; understanding of SOC 2 controls and data residency requirements
Infrastructure as Code: Proficiency with Terraform or CloudFormation; experience building CI/CD pipelines (CodePipeline, GitHub Actions, etc.) and applying GitOps practices
Ideally, You Also Have Several of the Following
ML Platform: Experience with SageMaker (Pipelines, Feature Store, Model Monitor, Endpoints), Bedrock, and MLOps patterns
Integration Patterns: REST/GraphQL API design, OpenAPI 3.0, asynchronous messaging, saga patterns, circuit breakers
Observability & Cost Optimization: CloudWatch, X-Ray, OpenTelemetry, APM dashboards; cost optimization using tools like Trusted Advisor and Cost Explorer

Solution Architect, System Architect

Key skills