Context
Transcarent operates a healthcare navigation platform that depends on reliable data flows from dozens of external partners. Integration delivery spanned engineering, analytics, customer success, and partner engineering — with production issues arriving daily.
Problem
The integration portfolio lacked consistent intake standards, shared visibility into pipeline health, and a single operating model for escalations. Leadership needed weekly reporting tied to measurable reliability targets, not status slides.
My role
Led requirements, intake, and delivery for the data integration portfolio — coordinating engineering, analytics, and 30+ partner teams on production reliability and technical direction for platform health.
Approach
- Set SLO/SLA targets for data quality and pipeline reliability across the portfolio
- Built an observability dashboard with query filters for pipeline health, data flow, and delivery performance — used in weekly reviews and leadership reporting
- Contributed to a P0 Redshift-to-Databricks migration: requirements, phased plan, dependency tracking
- Defined a Team Operating Model — intake standards, documentation structure, escalation paths
- Delivered team presentations on AI enablement for integration work (LLM workflows, prompt patterns, tool limits)
- Used AI-assisted workflows in requirements, triage notes, and status reporting
Outcome
Portfolio delivery became trackable against reliability targets. Leadership had a shared dashboard for weekly reviews. Migration work proceeded on a phased plan with dependencies visible. Team had clear intake and escalation paths instead of ad-hoc firefighting.