XLed cost, schedule, and performance of the design, development, testing, and deployment of software and secure cloud infrastructure capabilities for the Space Assets Program Office. Managed $90M in software deliverables and $250M in cloud infrastructure. Rapidly implemented a $50M Agile software re-baselining that averted a 24-month gap in mission capabilities. Ranked #1 of 20 Project Managers in 2021.
Delivery Scope
$90M
Design through deployment
Infrastructure
$250M
Secure infrastructure capabilities
Mission Recovery
$50M
Averted 24-month capability gap
Performance
#1/20
Project Managers, 2021
Impact
24 mo
Timeline Recovered
Access
TS/SCI
Classified Environments
XOwned and delivered multiple full-stack features across Pinterest's advertiser data infrastructure. Architected a KV Store data layer serving 1M+ daily requests with a 7x latency improvement (350ms → 49ms p99) and 40% success rate increase. Built event-driven data pipelines using Flink & Kafka for real-time advertiser data propagation. Optimized Airflow DAG execution, cutting pipeline runtime by 50% and reducing cloud compute costs by $12k annually. Operated in on-call rotation supporting distributed databases and microservices on AWS.
Performance gain
7x
350ms → 49ms p99
Efficiency
50%
Airflow DAGs: 5hr → 2.5hr
Infrastructure
60%
Caching strategy optimization
System scale
1M+
KV Store serving advertisers
Reliability
75%
On-call incident frequency
Cost Reduction
$12K
Annual cloud spend eliminated
XA full Extract → Transform → Load → Query → Visualize pipeline that fetches baseball player data from multiple sources (ESPN, Fangraphs, Baseball Savant), transforms with normalization, hydrations, and custom valuations (TRP — True Relative Price), loads to PostgreSQL, and serves through Hasura DDN (GraphQL). Visualization layer built with Plotly dashboards for in-season decision making.
XA native macOS application built in Swift/SwiftUI that opens an ESPN Draft Room and scrapes it in real-time for bidding activity and draft results. Concurrently, a separate Python thread hosts a Flask web service where the scraped data is served as a RESTful JSON API — enabling live decision-making during fantasy baseball auction drafts with up-to-the-second bid tracking.
Check out on GitHubArchitecture
2
Swift frontend + Python backend
API
REST
Flask JSON web service
Automation
Real-time
Live ESPN draft room parsing
Frontend
SwiftUI
Native macOS application
