Cloud, data, and AI engineering case studies

Selected work

• Making sensitive data loads traceable and safe to rerun: An AWS ETL foundation that keeps raw files, validates and quarantines bad rows, stages each run, and loads relational data transactionally.
• Scaling a Cloud Run API without overwhelming its database: A Cloud Run blueprint that coordinates instance scaling with database connection limits, restricts ingress, and separates multi-region compute from the single write-primary data design.
• Keeping AWS compliance evidence ready for review: A compliance-readiness blueprint that gathers configuration evidence continuously, routes findings by risk, and keeps framework mapping separate from certification.
• Planning EKS recovery without two active writers: A warm-standby EKS design that distinguishes replication from backup and uses a human-controlled failover runbook instead of promising untested RPO or RTO.
• Giving internal teams controlled access to shared EKS: An EKS blueprint for internal teams that layers Kubernetes RBAC, workload IAM, network policy and resource quotas instead of treating namespaces as hard tenant isolation.
• Designing releases around the artifact that passed testing: A pipeline blueprint that builds once, scans code and images, promotes by digest, ties Terraform apply to an approved plan, and defines rollback boundaries.
• Modernizing a live application without a forced cutover: A legacy application platform rebuilt on AWS with controlled releases, protected access, and a handover to the client.
• Sharing a cloud platform without sharing customer access: One Google Cloud platform for a cybersecurity product, with network and identity controls separating customer workloads.
• Rebuilding the data path behind conflicting reports: Fragmented pipelines rebuilt around Kafka, Snowflake, and tested transformations, with quality checks and traceable reporting.
• An incident assistant that can investigate but cannot act alone: An illustrative AI assistant that gathers incident evidence, proposes a diagnosis, and asks for approval before consequential actions.