Building Data Engineering Agent for IBM watsonx — leveraging latest techniques on LangChain, MCP, tool-calling, and context engineering.

Accomplishments: Top 15% performance rating. Recognized for rapid two-quarter delivery of new Python SDK for IBM Cloud Data Platform. Now in public beta: https://community.ibm.com/community/user/blogs/john-wen/2025/09/30/announcing-the-watsonxdata-integration-unified-pyt

• Designed and implemented a new scalable Pub/Sub and Apache Kafka queue-based hotel search system on Google Cloud, enabling the processing of 32 million search events per hour with zero dropped events and 95% cache accuracy during peak traffic.

• Deployed autoscaling Kubernetes pods and optimized performance by building Splunk and New Relic analysis dashboards, ensuring nearly 100% production uptime.

• Developed Maven libraries and Java Spring back-end services, improving code readability and maintainability through object-oriented design principles and JUnit testing.

• Parallelized legacy SQL Server algorithms by migrating key databases to Amazon Redshift and implementing queries optimized for columnar data storage, decreasing insurance loss calculation time by 90%.

• Developed new C# application workflows to integrate on-prem computing with AWS cloud infrastructure, advancing the company’s cloud migration strategy for big data workloads.

• Introduced real-time page updates using Google Firebase in React.js discussion forum used by Ohio school campaigns.

• Built Node.js server APIs and SQL queries for Postgres database to enable back-end user data aggregation.

• Designed and animated an interactive Next.js web app with Framer Motion, increasing user engagement and supporting sales teams in attracting and converting customers.