Peter Wong

I’m a Senior Data Engineer with 12+ years of experience building hyperscale data platforms across Google, Databricks, and healthcare at Optum. I focus on designing governed, AI-ready systems that improve performance, reduce cost, and accelerate time-to-insight in high-stakes environments.

At Optum, I architected HIPAA-compliant real-time streaming pipelines using Apache Kafka, Debezium CDC, and Databricks Spark Structured Streaming to process 5M+ patient events daily with sub-5-minute latency. I also designed and deployed medallion lakehouse architectures on Delta Lake with Unity Catalog governance and Apache Iceberg compatibility, reducing query latency by 75% and storage costs while supporting multimodal RAG and AI use cases.

I lead agentic AI-assisted data quality and observability with zero-ETL integrations, eliminating 90% of manual validation and achieving 99.99% data freshness SLAs across 200+ consumers. I optimize ELT orchestration with dbt and Apache Airflow for petabyte-scale datasets, and I’ve built production feature stores and contract-first ingestion capabilities that accelerate ML deployment cycles by 10x—backed by earlier lakehouse and streaming platform migrations at Databricks and foundational hyperscale pipelines on Google Cloud.