Frank Chang

Led the creation of Sydney Health, a cloud-native digital health platform serving 16 million users and delivering AI-driven personalized features like provider search, 24/7 telehealth, benefits and claims management, and social determinants of health check-ins. Architected and deployed microservices-based APIs integrating with FHIR/HL7-compliant EHR systems, reducing query latency by 30% through Redis caching. Engineered WebRTC-based telehealth capabilities facilitating 1.5 million virtual visits with HIPAA-compliant encryption and third-party integrations, achieving 98% case resolution in pilot programs. Implemented generative AI-powered Personalized Match algorithm and My Health Check-in NLP-driven questionnaires improving care access and resource matching. Constructed ETL pipelines processing 40 million monthly claims and SDOH data for real-time analytics. Streamlined CI/CD pipelines ensuring 99.99% uptime, cut deployment times by 40% through blue-green deployments. Integrated IoT w

Designed high-throughput data pipelines using Spark and Kafka to process trillions of daily metrics and logs for Datadog's observability platform, maintaining 99.99% uptime for over 28,000 customers across multi-cloud environments including AWS, Azure, and GCP. Optimized Spark jobs and Kafka configurations to reduce processing latency by 30% and increase throughput for high-volume telemetry data. Automated pipeline monitoring and alerting with Datadog tools, decreasing mean time to recovery (MTTR) by 35% for pipeline incidents. Collaborated with data engineering teams to create cost-efficient workflows leveraging Kubernetes and Terraform, reducing infrastructure costs by 20%. Enhanced pipeline reliability by introducing retry mechanisms and dead-letter queues, ensuring 100% data delivery for critical customer metrics and analytics. Led blameless postmortems to identify root causes and deploy preventative measures reducing pipeline failures by 40%. Mentored junior engineers in debugging

Built secure API endpoints using C# and .NET, reducing unauthorized access incidents by 40% for fintech platforms. Created real-time financial dashboards using Angular and D3.js, improving user data interaction speed by 30%. Configured Azure-based cloud security policies ensuring PCI DSS compliance for payment processing systems. Performed penetration testing and vulnerability assessments, resolving 95% of identified client application risks. Refined SIEM integration with Azure, shortening threat detection time by 25% through automated monitoring.