Led the end-to-end modernization of an enterprise data warehouse, migrating legacy on-prem data assets to a cloud data platform VERIFY: name platform?. Directed a cross-functional team of 12 engineers, architects, and BI developers alongside vendor integration partners. The program cut nightly batch processing time by 86%, reduced annual infrastructure cost by 48% VERIFY: $ figures ok to share?, and achieved 99.95% uptime with zero unplanned disruption at cutover.
| Item | Detail |
|---|---|
| Executive Sponsors | VERIFY title-level only, e.g. VP Data & Analytics, CIO |
| Baseline Infrastructure Cost | VERIFY |
| Target Infrastructure Cost | VERIFY |
| Target SLA | < 2.0 hour nightly load window (from 8.5 hours) |
Audited 1,200+ tables to map core facts, dimensions, staging tables, and downstream dashboard/integration dependencies.
Established a RACI framework across program scope, architecture, pipeline delivery, reconciliation, and cutover approval, with a 4-tier work breakdown structure spanning initiation through decommissioning.
Ran a 60-day parallel production execution across legacy and target systems, with automated daily reconciliation across row counts, checksums, and financial aggregates.
Executed a scheduled off-peak cutover with staged system freeze, final delta sync, reconciliation gate, endpoint switchover, and a formal go/no-go checkpoint before unlocking user access.
| Metric | Before | After | Change |
|---|---|---|---|
| Nightly ETL Window | 8.5 hrs | 1.2 hrs | 86% faster |
| Dashboard Query Latency | 45–90 sec | < 3 sec | 15x improvement |
| System Uptime SLA | 98.2% | 99.95% | Near-zero unplanned downtime |
| User Adoption | — | 94% MAU | VERIFY vs. scope figure |