Rafael Ortega

About

Backend/data engineer with hands-on production experience building FastAPI Python APIs and AWS-native platforms (Lambda/API Gateway, SQS, ECS Fargate) with Terraform + GitHub Actions CI/CD and strong reliability practices (JWT/RBAC, retries/timeouts, structured errors/logging). Also built AWS Glue ETL pipelines (S3/RDS to curated S3/Athena) with schema evolution and data quality controls, modernized legacy processing via parallel-run validation and phased cutovers, and has demonstrated SQL tuning impact (seconds to <200ms) plus incident ownership for batch pipeline SLAs.

Key Strengths

• Designed stateless, containerized FastAPI services behind a load balancer
• Implemented JWT auth with RBAC enforced via middleware
• Reliability engineering for downstream calls (timeouts, retries with exponential backoff, anti-cascading safeguards)
• Centralized exception handling with consistent client errors and structured logging
• Delivered AWS serverless + container architecture (Lambda/API Gateway, SQS-triggered Lambdas, ECS Fargate)
• Built Terraform + GitHub Actions CI/CD with runtime secrets via Secrets Manager/Parameter Store
• ETL expertise with AWS Glue (crawlers/catalog, Spark jobs), schema evolution, data quality quarantine, and bookmark-based reprocessing
• Modernized legacy workflows into Python services with parallel-run parity validation and phased cutover using feature flags/rollback
• SQL performance tuning using execution plans, indexing, and query rewrites; reduced a query from seconds to <200ms
• Owned and resolved a batch pipeline SLA incident using CloudWatch alerts, partition-level reruns, and preventive controls (input-size checks, batch sizing, alert tuning)

Reference Highlights

• Strong technical skills (Python, SQL, distributed data processing)
• Clear understanding of API design principles
• Ensures code quality through testing
• Optimizes systems for performance and scalability
• Delivered major processing-time reduction (hours to minutes) via real-time APIs
• Improved system reliability and performance
• Solid AWS Glue ETL experience
• Builds modular, well-documented ETL jobs
• Implements automated monitoring to catch failures early
• Strong with relational databases and complex SQL
• Improved reporting pipeline performance via query rewrites and indexing
• Careful, low-risk migration approach (validation tests, incremental rollouts)
• Proactive monitoring and logging; reliable scheduled processing
• Clear communicator with technical and non-technical stakeholders
• End-to-end ownership of backend components
• Very effective building and maintaining production Python APIs
• Delivered stable, low-latency, maintainable FastAPI service
• Reduced production issues through strong validation and centralized error handling
• Designed services to scale smoothly (stateless, well-monitored)
• Strong hands-on AWS development skills
• Implemented IaC-driven deployments with CI/CD for consistent releases
• Proactive security mindset (least-privilege IAM, Secrets Manager)
• Reliable and maintainable AWS Glue ETL pipelines
• Strong data quality focus (schema validation, checks, clear logging)
• Handled ETL failures effectively (retries, alerts, targeted reprocessing)
• Very strong with relational databases and complex SQL
• Improved query performance significantly (seconds to sub-second) via execution plan/index/join optimization
• Methodical, low-risk legacy modernization (parallel runs, phased rollout, rollback plans)
• Strong production operations readiness (monitoring, logging, alerting)
• High ownership during incidents (early detection, end-to-end resolution)
• Clear communication with technical and non-technical stakeholders
• Adapts communication style to audience
• Creates clear documentation (diagrams and pseudocode) that aids understanding

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