Selected work
Experience Digital
Cross-functional engineering work spanning legacy modernization, frontend performance, DevOps, and cloud data platform delivery across application and infrastructure layers.
- Modernized legacy product surfaces while keeping compatibility with existing systems and database constraints.
- Improved React application performance and user experience through more disciplined frontend optimization.
- Moved into DevOps and platform work across CI/CD, infrastructure automation, observability, and delivery workflows.
- Contributed to data platform architecture for Power BI workloads across Azure and AWS.
What it is
Experience Digital was a period of broad engineering work across product delivery, infrastructure, and data systems.
The work started with hands-on software engineering in legacy and modern web applications, including database changes, API integration, and incremental product modernization. From there, the role expanded into frontend performance work, DevOps delivery, and cloud data platform architecture.
Instead of staying confined to one layer of the stack, this work moved across application engineering, deployment systems, and reporting infrastructure.
Why it matters
This experience mattered because it forced the engineering work beyond feature delivery alone.
It required handling:
- legacy constraints without freezing progress
- frontend performance without shallow optimization theater
- CI/CD and infrastructure concerns that affect delivery speed and reliability
- cloud data architecture that had to support reporting workflows across AWS and Azure
That combination sharpened the ability to connect product implementation with the systems that actually keep software shippable and usable.
Technical shape
The technical shape evolved across several layers:
- Application modernization: Updating legacy systems, extending schemas, integrating APIs, and introducing newer application patterns with Next.js, Tailwind, Jotai, tRPC, and Prisma.
- Frontend performance: Improving React application behavior with better state and rendering discipline to reduce load and interaction friction.
- DevOps and delivery: Supporting CI/CD pipelines, infrastructure automation, and cross-functional release flow to reduce operational drag.
- Cloud data platform work: Contributing to data lake and reporting architecture for Power BI environments spanning Azure and AWS.
The value of this work was not any single framework or tool. It was the ability to move across product code, delivery systems, and platform concerns without losing engineering clarity.