Joseph Wonesh

About

Backend/data engineer focused on production-grade Python microservices and AWS platforms, including a hybrid Lambda + ECS Fargate architecture managed with Terraform and CI/CD. Has hands-on reliability experience (JWT/OAuth, timeouts, retries, centralized error classification) and built AWS Glue/PySpark ETL pipelines consolidating PostgreSQL/RDS, MongoDB, and S3 sources into curated partitioned Parquet datasets. Demonstrated measurable SQL tuning impact (8 minutes to 25 seconds) and disciplined legacy-to-modern migrations with parity validation and UAT sign-off.

Experience

Education

Key Strengths

• Designed and operated Python FastAPI microservices on AWS with clean separation of concerns
• Reliability engineering for APIs: JWT/OAuth auth, local key caching, strict timeouts, transient-only retries with exponential backoff
• Reduced cascading failures by implementing centralized error classification/mapping and retriable-flagged exceptions
• Delivered hybrid AWS architecture (Lambda + ECS Fargate) with Terraform IaC and CI/CD (tests, Docker builds, plan/apply)
• Strong secrets/config management using SSM Parameter Store, Secrets Manager, and OIDC-based IAM role assumption
• Built multi-source AWS Glue/PySpark ETL to curated, partitioned Parquet datasets with data quality gates
• Modernization/migration discipline: checksum validation, sampling, parallel runs, stakeholder demos and UAT sign-off
• SQL performance optimization with indexing/partitioning/query rewrites; improved reporting query runtime from ~8 minutes to ~25 seconds
• Production incident ownership for batch pipelines: alert-driven detection, log/metric triage, customer comms, fallback extraction and monitoring improvements