Russell Wong

About

Backend/data engineer with experience on large-scale consumer platforms (Google and Meta), building high-traffic Python microservices (REST/gRPC) on Kubernetes with strong reliability/observability practices. Delivered AWS container-based deployments with CI/CD and IaC, and built AWS Glue ETL pipelines on S3 with schema evolution and data quality controls; also has demonstrated SQL tuning impact (15% latency reduction) and incident ownership for batch pipelines.

Key Strengths

• Designed and operated high-traffic stateless Python microservices on Kubernetes with REST + gRPC
• Strong reliability engineering: timeouts, bounded retries with jitter, deadline propagation, circuit breakers
• Security-minded service authN/authZ using short-lived credentials and gateway + middleware enforcement
• Production observability at scale: structured logs, distributed tracing, p99/p999 latency metrics
• Built AWS Glue ETL on S3 with schema evolution, embedded data quality checks, and idempotent partition writes
• Modernized monolithic/legacy workflows into microservices using shadow-mode parity validation and safe cutover (feature flags, ramp-up, rollback)
• SQL performance tuning with measured impact (15% response time reduction on Meta News Feed queries)
• Owned and mitigated batch/data pipeline incident via monitoring-driven triage; implemented adaptive partitioning/backpressure to prevent recurrence

Reference Highlights

• Highly effective building production Python services/APIs
• Delivers reliable, scalable services
• Strong ownership of performance, observability, and maintainability
• Strong hands-on AWS experience operating production systems
• Designs for high availability and stability under heavy traffic
• Applies least-privilege and secure configurations
• Builds reliable, maintainable ETL pipelines with proactive data quality handling
• Strong with relational databases and complex SQL optimization
• Effective at modernizing legacy systems into well-defined microservices
• Strong validation and risk management during migrations (shadow runs, incremental rollout, fast rollback)
• Strong production operations readiness (monitoring, log analysis, alerting)
• High ownership during incidents; leads triage and mitigation
• Follows through with RCA and long-term prevention improvements
• Communicates clearly with technical and non-technical stakeholders
• Clear, concise, actionable technical documentation
• Business impact: improved recommendation accuracy and increased daily video views

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