22 years building and operating mission-critical systems for regulated industries — finance, insurance, mainframe modernization. Led an 18-engineer cloud migration program; previously owned ITIL operations across 150 applications with 14 direct and ~50 indirect reports; architected IMS-DB systems handling 1M+ transactions/hour. Rare bridge between deep mainframe expertise (COBOL, PL/I, IMS-DB, DB2 z/OS) and modern cloud-native delivery (AWS, Next.js, Python, Supabase). Currently building AI-augmented tools that accelerate mainframe modernization.
Own the technical direction for an Enterprise Reinsurance modernization program — an ongoing multi-year migration of a 25+ year-old mainframe system carrying billions in treaty exposure to AWS, without a write freeze for the actuarial and finance teams that depend on it daily. Lead 18 engineers across data, application, and reporting tracks. Designed the metadata-driven migration pattern, built the event-driven reporting layer feeding ~50 treaty and finance consumers, and shipped the Cash Clearance app end-to-end on serverless TypeScript + Aurora Postgres. Cut Cash Clearance search latency from 3–5 minutes to under 5 seconds on 100K+ row queries.
Owned the L1–L3 application operations across a 150-system portfolio under an ITIL delivery model, with 14 direct reports and ~50 indirect reports. Stood up rigorous log monitoring, proactive alerting, and operational dashboards so the team caught issues before users did. Drove a continuous-improvement loop — identifying repeat incidents, root-causing them, and shipping permanent fixes rather than re-running the same triage. Improved portfolio stability by 60% over three years.
Owned the business-logic analysis track on a major rating-engine re-platform for a US personal-lines carrier — paired daily with actuarial SMEs to translate 100+ hardcoded PL/I + IMS-DB rules into Ratabase algorithms, replacing engineering round-trips with a system the business could maintain themselves. Ran re-rate cycles across full state policy books when original or renewal rating errors surfaced; individual corrections returned up to several hundred thousand dollars in customer refunds. Designed and implemented predictive-analytics datasets (Informatica + PowerExchange) with the Principal architect, feeding actuarial pricing and underwriting decisioning.
Entry into regulated-industry tech — production support and feature work on P&C insurance applications at Cognizant. Performed DB2 SQL performance tuning on claims workloads, requirements analysis with business analysts, and quality audits across the application portfolio. The foundation in mainframe-adjacent data layers, regulated-industry release discipline, and customer-money systems that every later role built on.
Designed a metadata-driven ETL architecture: 3 generalized Glue jobs (extract, transform, load) covering all 23 source tables — instead of the obvious 3-per-table design (~69 jobs) the team would have built by default. Architected the dual-pipeline split: AWS DMS for one-time historical migration off mainframe DB2-LUW; Glue/PySpark for ongoing ELT and the reporting layer — no DMS dependency on reporting.
Cut search query latency from 3–5 minutes to under 5 seconds — even for result sets exceeding 100K rows — via DynamoDB caching of search results and PostgreSQL core-table splitting for partitioned reads. Designed a hybrid sync/async execution model in the Lambda backend — interactive flows stay responsive while heavy workloads run async.
Sourced premium and loss data from 12 heterogeneous systems (mainframe COBOL files, DB2 z/OS, MSSQL) into a single analytics-ready layer on Teradata. Established the PowerExchange connections and mapped incoming records against COBOL copybook layouts — the deepest technical lift on the program.
Translated 100+ complex mathematical rating algorithms to system requirements. Migrated legacy rating engine from Corporate Rating System to Ratabase.
6 tools: list databases / list schemas / list tables / describe table / query / explain plan / copybook mapper. Defence-in-depth read-only: connection-level readonly=True AND statement-prefix allow-list (rejects EXEC, MERGE, etc.).
Invite-code onboarding — 2-step registration vs. 5-step traditional flow. Row-Level Security on every Supabase table for data isolation.