Rayon Myrie

Architected Snowflake-based enterprise healthcare analytics pipelines, improving data delivery efficiency by 12% through SQL transformation optimization and standardized ingestion patterns. Designed 25 scalable ETL pipelines integrating 8 medical device, quality, and operational source systems.

Architected a Confluent Platform streaming environment for medical device telemetry, improving event delivery latency by 12% through Kafka broker sizing, partition distribution, and multi-AZ replication design. Designed 12 ingestion workflows using Kafka Connect distributed workers and standardized source configurations.

Led Kafka streaming architecture for medical device supply chain visibility, improving event processing efficiency by 16% through partition key design, producer batching, and consumer concurrency optimization. Integrated 15 enterprise APIs and operational databases through Kafka Connect JDBC connectors and Schema Registry.

Designed Azure Databricks and Snowflake data architecture for medical device operational analytics, reducing reporting preparation effort by 16% through standardized ingestion and reusable PySpark transformations. Integrated 12 ingestion workflows across ERP, manufacturing quality, service, and external systems.

Designed healthcare ETL architecture integrating 6 clinical and operational systems through Python, SQL, and Snowflake to support patient encounter analytics. Built 15 clinical data pipelines using Airflow scheduling and Python transformation services.

Designed a Kafka-based healthcare event platform integrating 8 clinical and operational systems, using Confluent Schema Registry and Kafka Connect to standardize patient service event ingestion. Improved streaming data freshness by 17% through Kafka consumer tuning and partition distribution.

Designed Kafka event ingestion for 4 retail channels, integrating order, inventory, and fulfillment events using Kafka Connect and standardized topics. Improved order event processing latency by 15% through producer batching, compression, and partition key optimization.

Designed retail analytics ETL workflows integrating 8 e-commerce, inventory, and order management sources using SQL and Python. Improved order analytics processing efficiency by 15% through incremental Snowflake ingestion and SQL transformation refactoring.

Designed benefits administration data integration workflows for 6 enterprise clients using SQL Server, Python, and standardized source mappings. Implemented 18 scheduled ETL jobs integrating eligibility, enrollment, and demographic records.

Designed event-driven integrations for 6 enterprise benefits clients using Apache Kafka, JDBC source connectors, and structured schemas. Reduced client data reconciliation effort by 16% through Python validation, Kafka event deduplication, and SQL exception reporting.

Developed enterprise benefits analytics pipelines integrating 10 employer and vendor datasets using Oracle SQL, Python, and standardized transformation procedures. Reduced recurring benefits reconciliation exceptions by 14% through SQL validation checks.

Established data integration architecture for 8 benefits reporting sources using SQL, Python, and Apache Kafka. Improved data processing consistency by 14% through schema validation, transformation controls, and exception handling.

Mapped 12 client benefits data feeds using SQL profiling, source-to-target specifications, and transformation rules. Reduced data mapping errors by 13% through automated SQL validation and standardized field normalization.

Configured data transformation workflows for 5 benefits implementation projects using SQL Server, file mapping specifications, and structured eligibility validation. Integrated 12 benefits enrollment file layouts using relational staging tables.

Developed client reporting workflows across 6 operational systems using SQL, ETL processes, and relational data modeling. Reduced recurring data exceptions by 15% through SQL reconciliation and validation rules.

Developed client service reporting workflows spanning 8 operational data sources using SQL Server, stored procedures, and standardized extracts. Reduced recurring reporting preparation effort by 15% through SQL query refactoring.

Configured benefits administration workflows for 4 client implementations using SQL, application rules, and structured test cases. Reduced configuration defects by 12% through automated validation queries and boundary-condition testing.

Configured benefits administration data rules across 6 client implementations using SQL queries, eligibility mappings, and system configuration tables. Reduced recurring configuration defects by 12% through SQL-based validation.

Developed university administrative applications integrating 4 departmental databases using SQL, server-side programming, and relational design. Reduced manual administrative processing effort by 13% through SQL-driven automation.

Developed university software supporting 3 administrative workflows using Java, SQL, and relational database design. Reduced application response time by 14% through SQL query optimization and database indexing.

Completed the Sarbanes-Oxley (SOX) ITGC Audit Concepts and Coordination course on Udemy in June 2025.

Completed the Sarbanes-Oxley (SOX) ITGC Audit Concepts and Coordination course on Udemy in June 2025.

Completed the Azure Databricks End to End Project with Unity Catalog CICD course on Udemy in February 2024.

Completed the Azure Databricks End to End Project with Unity Catalog CICD course on Udemy in February 2024.

Master of Science in Computer Science from New Jersey Institute of Technology, completed in 2020.

Master of Science in Computer Science from New Jersey Institute of Technology, completed in 2020.

Master of Science in Data Science from New Jersey Institute of Technology, completed in January 2020.

Master of Science in Data Science from New Jersey Institute of Technology, completed in January 2020.

Master's Certificate in Data Mining and Machine Learning from New Jersey Institute of Technology, completed in 2018.

Master's Certificate in Data Mining and Machine Learning from New Jersey Institute of Technology, completed in 2018.

Completed the Driving Business Results with Big Data course from SAP in June 2015.

Completed the Driving Business Results with Big Data course from SAP in June 2015.

Bachelor of Arts in Computer Science with a Math Minor from Rutgers, The State University of New Jersey-Newark, completed in 2004.

Bachelor of Arts in Computer Science with a Math Minor from Rutgers University-Newark, completed in 2004.

Associate of Applied Science in Applied Computer Science and a Certificate in Web Design from Passaic County Community College, completed in 2000.

Associate of Applied Science in Applied Computer Science and a Certificate in Web Design from Passaic County Community College, completed in 2000.