Antoine Tan

About

Backend/data engineer who has owned production Python APIs and high-throughput async workflows on AWS (FastAPI, Docker, ECS/EKS/Lambda) with mature reliability practices like idempotency, bounded retries, circuit breakers, and strong observability. Also built AWS Glue ETL into an S3/Redshift lakehouse and modernized legacy batch systems via parallel-run parity testing and feature-flagged migrations, including a SQL tuning win cutting a multi-minute query to under 10 seconds.

Experience

Education

Key Strengths

• Designed and operated production FastAPI services on AWS with strong reliability patterns (timeouts, bounded retries, idempotency, circuit breakers)
• Built hybrid serverless/container AWS deployments with Terraform-based IaC and CI/CD (ECR, ECS rolling deploys, Lambda versioning/aliases)
• Strong security and configuration practices (JWT/OAuth2, tenant/role enforcement, IAM-scoped access, SSM Parameter Store, Secrets Manager)
• Implemented observability and incident readiness (health checks, metrics/tracing, dashboards/alerts, runbooks tied to PRs/postmortems)
• ETL/data engineering on AWS Glue into S3/Redshift with schema evolution controls, data quality validation, quarantine flows, and idempotent reruns
• Modernized legacy batch processing into Python services with parallel-run parity validation and incremental migration behind feature flags
• SQL performance optimization with measured impact (reduced query runtime from minutes to <10 seconds via indexes, query rewrite, partitioning)
• Owned production incident response for data pipelines (detected via CloudWatch + freshness metrics; mitigated with pauses/backfill; prevented via schema validation and contract tests)