About Me
I'm a software engineer with a B.S. in Bioinformatics from UC San Diego and a career that spans data engineering and full-stack development. I've built Go ETL pipelines processing clinical research data at scale, and led full-stack development of a spatial biology visualization platform — owning everything from gRPC service design to React/Next.js frontend and in-browser analytics performance.
I'm drawn to technically complex, science-adjacent problems where the software has to meet the data halfway. Whether it's designing a distributed workflow for Glacier archive restores or squeezing 40ms out of a DuckDB-wasm query path, I care about getting the details right.
Skills
Experience
▸Introduced, developed, and maintained Apache Airflow (AWS MWAA) as the orchestration backbone of the data platform — going from zero to owning the full DAG ecosystem for clinical research dataset generation pipelines.
▸Became proficient in Go through ownership of the team's ETL platform, with particular depth in pipeline optimization and Go memory management — reducing EKS pod memory usage by up to 30% by offloading in-memory work to AWS managed services.
▸Led first real Terraform ownership: reduced the codebase's Terraform file count by 94% (520 → 29) under a new infrastructure model combining Go binaries (Bazel), Airflow DAGs (Python), and Kubernetes pod operators (EKS).
▸Designed Docker-based test environments and S3 branch-state synchronizations that reduced integration testing turnaround from days to hours, directly improving developer velocity.
▸Built and maintained Go-based ad metrics ETL pipelines processing revenue and engagement data for thousands of publisher sites, gaining strong exposure to the scale and reliability demands of adtech data infrastructure.
▸Developed hands-on AWS fluency across Kinesis (real-time ingestion), Redshift (analytics warehouse), S3, and SNS — working directly with the services that underpin high-throughput data pipelines.
▸First professional introduction to data pipelines: built an Apache Airflow workflow in Python to automate PHI scrubbing of MySQL databases via Bash and SQL scripts, deployed on AWS with Docker.